메뉴 건너뛰기




Volumn , Issue , 2009, Pages 213-226

Recent advances in efficient learning of recurrent networks

Author keywords

[No Author keywords available]

Indexed keywords

EFFICIENT LEARNING; HUMAN BRAIN; LONG-TERM DEPENDENCIES; OR-CAUSALITY; RECURRENT NETWORKS; RECURRENT NEURAL NETWORK (RNNS); SPATIO-TEMPORAL DATA; TRAINING ALGORITHMS;

EID: 84887010605     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (25)

References (162)
  • 2
    • 50449099550 scopus 로고    scopus 로고
    • Event detection and localization for small mobile robots using Reservoir Computing
    • E. A. Antonelo, B. Schrauwen, and D. Stroobandt. Event detection and localization for small mobile robots using Reservoir Computing. Neural Networks, 21(6):862-871, 2008.
    • (2008) Neural Networks , vol.21 , Issue.6 , pp. 862-871
    • Antonelo, E.A.1    Schrauwen, B.2    Stroobandt, D.3
  • 3
    • 41849095655 scopus 로고    scopus 로고
    • Dynamical constraints on using precise spike timing to compute in recurrent cortical networks
    • A. Banerjee, P. Serie's, and A. Pouget. Dynamical constraints on using precise spike timing to compute in recurrent cortical networks. Neural Computation, 20(4):974-993, 2008.
    • (2008) Neural Computation , vol.20 , Issue.4 , pp. 974-993
    • Banerjee, A.1    Serie's, P.2    Pouget, A.3
  • 4
    • 54349093123 scopus 로고    scopus 로고
    • A nonfeasible gradient projection recurrent neural network for equality-constrained optimization problems
    • M. P. Barbarosou and N. G. Maratos. A nonfeasible gradient projection recurrent neural network for equality-constrained optimization problems. IEEE Trans. on Neural Networks, 19(10):1665-1677, 2008.
    • (2008) IEEE Trans. On Neural Networks , vol.19 , Issue.10 , pp. 1665-1677
    • Barbarosou, M.P.1    Maratos, N.G.2
  • 5
    • 29444457388 scopus 로고    scopus 로고
    • Locally recurrent neural networks for long-term wind speed and power prediction
    • T. G. Barbounis and J. B. Theocharis. Locally recurrent neural networks for long-term wind speed and power prediction. Neurocomputing, 69(4-6):466-496, 2006.
    • (2006) Neurocomputing , vol.69 , Issue.4-6 , pp. 466-496
    • Barbounis, T.G.1    Theocharis, J.B.2
  • 6
    • 33847369874 scopus 로고    scopus 로고
    • A locally recurrent fuzzy neural network with application to the wind speed prediction using spatial correlation
    • T. G. Barbounis and J. B. Theocharis. A locally recurrent fuzzy neural network with application to the wind speed prediction using spatial correlation. Neurocomputing, 70(7-9):1525-1542, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.7-9 , pp. 1525-1542
    • Barbounis, T.G.1    Theocharis, J.B.2
  • 8
    • 33646811213 scopus 로고    scopus 로고
    • When response variability increases neural network robustness to synaptic noise
    • G. Basalyga and E. Salinas. When response variability increases neural network robustness to synaptic noise. Neural Computation, 18(6):1349-1379, 2006.
    • (2006) Neural Computation , vol.18 , Issue.6 , pp. 1349-1379
    • Basalyga, G.1    Salinas, E.2
  • 9
    • 33845348922 scopus 로고    scopus 로고
    • Parameter space structure of continuous-time recurrent neural networks
    • R. D. Beer. Parameter space structure of continuous-time recurrent neural networks. Neural Computation, 18(12):3009-3051, 2006.
    • (2006) Neural Computation , vol.18 , Issue.12 , pp. 3009-3051
    • Beer, R.D.1
  • 10
    • 33750417685 scopus 로고    scopus 로고
    • Wavelet-based nonlinear multiscale decomposition model for electricity load forecasting
    • D. Benaouda, F. Murtagh, J. Starck, and O. Renaud. Wavelet-based nonlinear multiscale decomposition model for electricity load forecasting. Neurocomputing, 70(1-3):139-154, 2006.
    • (2006) Neurocomputing , vol.70 , Issue.1-3 , pp. 139-154
    • Benaouda, D.1    Murtagh, F.2    Starck, J.3    Renaud, O.4
  • 13
    • 33646397012 scopus 로고    scopus 로고
    • How noise affects the synchronization properties of recurrent networks of inhibitory neurons
    • N. Brunel and D. Hansel. How noise affects the synchronization properties of recurrent networks of inhibitory neurons. Neural Computation, 18(5):1066-1110, 2006.
    • (2006) Neural Computation , vol.18 , Issue.5 , pp. 1066-1110
    • Brunel, N.1    Hansel, D.2
  • 14
  • 16
    • 34249714893 scopus 로고    scopus 로고
    • Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm
    • X. Cai, N. Zhang, G. K. Venayagamoorthy, and D. C. Wunsch II. Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm. Neurocomputing, 70(13-15):2342-2353, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.13-15 , pp. 2342-2353
    • Cai, X.1    Zhang, N.2    Venayagamoorthy, G.K.3    Wunsch II, D.C.4
  • 17
    • 33947139816 scopus 로고    scopus 로고
    • Global asymptotical stability of recurrent neural networks with multiple discrete delays and distributed delays
    • J. Cao, K. Yuan, and H. Li. Global asymptotical stability of recurrent neural networks with multiple discrete delays and distributed delays. IEEE Transactions on Neural Networks, 17(6):1646-1651, 2006.
    • (2006) IEEE Transactions On Neural Networks , vol.17 , Issue.6 , pp. 1646-1651
    • Cao, J.1    Yuan, K.2    Li, H.3
  • 18
    • 40649110282 scopus 로고    scopus 로고
    • On the implicit acquisition of a context-free grammar by a simple recurrent neural network
    • B. Cartling. On the implicit acquisition of a context-free grammar by a simple recurrent neural network. Neurocomputing, 71(7-9):1527-1537, 2008.
    • (2008) Neurocomputing , vol.71 , Issue.7-9 , pp. 1527-1537
    • Cartling, B.1
  • 19
    • 34548637276 scopus 로고    scopus 로고
    • Asymptotic behavior and synchronizability characteristics of a class of recurrent neural networks
    • C. Cebulla. Asymptotic behavior and synchronizability characteristics of a class of recurrent neural networks. Neural Computation, 19(9):2492-2514, 2007.
    • (2007) Neural Computation , vol.19 , Issue.9 , pp. 2492-2514
    • Cebulla, C.1
  • 20
    • 33847104144 scopus 로고    scopus 로고
    • Organization of the state space of a simple recurrent network before and after training on recursive linguistic structures
    • M. Cernansky, M. Makula, and L. Benuskova. Organization of the state space of a simple recurrent network before and after training on recursive linguistic structures. Neural Networks, 20(2):236-244, 2007.
    • (2007) Neural Networks , vol.20 , Issue.2 , pp. 236-244
    • Cernansky, M.1    Makula, M.2    Benuskova, L.3
  • 21
    • 36549005113 scopus 로고    scopus 로고
    • Global exponential periodicity and global exponential stability of a class of recurrent neural networks with various activation functions and time-varying delays
    • B. Chen and J. Wang. Global exponential periodicity and global exponential stability of a class of recurrent neural networks with various activation functions and time-varying delays. Neural Networks, 20(10):1067-1080, 2007.
    • (2007) Neural Networks , vol.20 , Issue.10 , pp. 1067-1080
    • Chen, B.1    Wang, J.2
  • 22
    • 36348966026 scopus 로고    scopus 로고
    • Global μ-stability of delayed neural networks with unbounded time-varying delays
    • T. Chen and L. Wang. Global μ-stability of delayed neural networks with unbounded time-varying delays. IEEE Transactions on Neural Networks, 18(6):1836-1840, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.6 , pp. 1836-1840
    • Chen, T.1    Wang, L.2
  • 23
    • 54349097207 scopus 로고    scopus 로고
    • Quasi-Lagrangian neural network for convex quadratic optimization
    • G. Costantini, R. Perfetti, and M. Todisco. Quasi-Lagrangian neural network for convex quadratic optimization. IEEE Transactions on Neural Networks, 19(10):1804-1809, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.10 , pp. 1804-1809
    • Costantini, G.1    Perfetti, R.2    Todisco, M.3
  • 25
    • 33846085516 scopus 로고    scopus 로고
    • Backpropagation algorithms for a broad class of dynamic networks
    • O. De Jesus and M. T. Hagan. Backpropagation algorithms for a broad class of dynamic networks. IEEE Transactions on Neural Networks, 18(1):14-27, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.1 , pp. 14-27
    • de Jesus, O.1    Hagan, M.T.2
  • 26
    • 34249668888 scopus 로고    scopus 로고
    • Nonlinear system identification with recurrent neural networks and dead-zone Kalman filter algorithm
    • J. de Jesus Rubio and W. Yu. Nonlinear system identification with recurrent neural networks and dead-zone Kalman filter algorithm. Neurocomputing, 70(13-15):2460-2466, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.13-15 , pp. 2460-2466
    • de Jesus Rubio, J.1    Yu, W.2
  • 27
    • 34548609011 scopus 로고    scopus 로고
    • Collective behavior of a small-world recurrent neural system with scale-free distribution
    • Z. Deng and Y. Zhang. Collective behavior of a small-world recurrent neural system with scale-free distribution. IEEE Transactions on Neural Networks, 18(5):1364-1375, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.5 , pp. 1364-1375
    • Deng, Z.1    Zhang, Y.2
  • 28
    • 34247526797 scopus 로고    scopus 로고
    • A model of the illusory contour formation based on dendritic computation
    • D. Domijan, M. Setic, and D. Svegar. A model of the illusory contour formation based on dendritic computation. Neurocomputing, 70(10-12):1977-1982, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.10-12 , pp. 1977-1982
    • Domijan, D.1    Setic, M.2    Svegar, D.3
  • 31
    • 33646117248 scopus 로고    scopus 로고
    • Influence of the neural network topology on the learning dynamics
    • F. Emmert-Streib. Influence of the neural network topology on the learning dynamics. Neurocomputing, 69(10-12):1179-1182, 2006.
    • (2006) Neurocomputing , vol.69 , Issue.10-12 , pp. 1179-1182
    • Emmert-Streib, F.1
  • 32
    • 40649098781 scopus 로고    scopus 로고
    • Syntactic systematicity in sentence processing with a recurrent self-organizing network
    • I. Farkas and M. W. Crocker. Syntactic systematicity in sentence processing with a recurrent self-organizing network. Neurocomputing, 71(7-9):1172-1179, 2008.
    • (2008) Neurocomputing , vol.71 , Issue.7-9 , pp. 1172-1179
    • Farkas, I.1    Crocker, M.W.2
  • 34
    • 33847342952 scopus 로고    scopus 로고
    • Generalized locally recurrent probabilistic neural networks with application to text-independent speaker verification
    • T. D. Ganchev, D. K. Tasoulis, M. N. Vrahatis, and N. D. Fakotakis. Generalized locally recurrent probabilistic neural networks with application to text-independent speaker verification. Neurocomputing, 70(7-9):1424-1438, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.7-9 , pp. 1424-1438
    • Ganchev, T.D.1    Tasoulis, D.K.2    Vrahatis, M.N.3    Fakotakis, N.D.4
  • 35
    • 44349174446 scopus 로고    scopus 로고
    • Equilibria and their bifurcations in a recurrent neural network involving iterates of a transcendental function
    • B. Gao and W. Zhang. Equilibria and their bifurcations in a recurrent neural network involving iterates of a transcendental function. IEEE Transactions on Neural Networks, 19(5):782-794, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.5 , pp. 782-794
    • Gao, B.1    Zhang, W.2
  • 36
    • 51349159817 scopus 로고    scopus 로고
    • Random neural networks with synchronized interactions
    • E. Gelenbe and S. Timotheou. Random neural networks with synchronized interactions. Neural Computation, 20(9):2308-2324, 2008.
    • (2008) Neural Computation , vol.20 , Issue.9 , pp. 2308-2324
    • Gelenbe, E.1    Timotheou, S.2
  • 37
    • 34247242721 scopus 로고    scopus 로고
    • An augmented extended Kalman filter algorithm for complex-valued recurrent neural networks
    • S. L. Goh and D. P. Mandic. An augmented extended Kalman filter algorithm for complex-valued recurrent neural networks. Neural Computation, 19(4):1039-1055, 2007.
    • (2007) Neural Computation , vol.19 , Issue.4 , pp. 1039-1055
    • Goh, S.L.1    Mandic, D.P.2
  • 39
    • 36248979779 scopus 로고    scopus 로고
    • Elman backpropagation as reinforcement for simple recurrent networks
    • A. Gruning. Elman backpropagation as reinforcement for simple recurrent networks. Neural Computation, 19(11):3108-3131, 2007.
    • (2007) Neural Computation , vol.19 , Issue.11 , pp. 3108-3131
    • Gruning, A.1
  • 40
    • 34247515219 scopus 로고    scopus 로고
    • Ranking neurons for mining structure-activity relations in biological neural networks: NeuronRank
    • T. Gurel, L. De Raedt, and S. Rotter. Ranking neurons for mining structure-activity relations in biological neural networks: NeuronRank. Neurocomputing, 70(10-12):1897-1901, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.10-12 , pp. 1897-1901
    • Gurel, T.1    de Raedt, L.2    Rotter, S.3
  • 44
    • 15844429145 scopus 로고    scopus 로고
    • Input space bifurcation manifolds of recurrent neural networks
    • R. Haschke and J. J. Steil. Input space bifurcation manifolds of recurrent neural networks. Neurocomputing, 64C:25-38, 2005.
    • (2005) Neurocomputing , vol.64 , pp. 25-38
    • Haschke, R.1    Steil, J.J.2
  • 45
    • 34247647196 scopus 로고    scopus 로고
    • Temporal pattern identification using spike-timing dependent plasticity
    • F. Henry, E. Dauce, and H. Soula. Temporal pattern identification using spike-timing dependent plasticity. Neurocomputing, 70(10-12):2009-2016, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.10-12 , pp. 2009-2016
    • Henry, F.1    Dauce, E.2    Soula, H.3
  • 46
    • 34047178025 scopus 로고    scopus 로고
    • A recurrent neural network for hierarchical control of interconnected dynamic systems
    • Z. Hou, M. M. Gupta, P. N. Nikiforuk, M. Tan, and L. Cheng. A recurrent neural network for hierarchical control of interconnected dynamic systems. IEEE Transactions on Neural Networks, 18(2):466-481, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.2 , pp. 466-481
    • Hou, Z.1    Gupta, M.M.2    Nikiforuk, P.N.3    Tan, M.4    Cheng, L.5
  • 47
    • 34249654548 scopus 로고    scopus 로고
    • Time series prediction with a weighted bidirectional multi-stream extended Kalman filter
    • X. Hu, D. V. Prokhorov, and D. C. Wunsch II. Time series prediction with a weighted bidirectional multi-stream extended Kalman filter. Neurocomputing, 70(13-15):2392-2399, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.13-15 , pp. 2392-2399
    • Hu, X.1    Prokhorov, D.V.2    Wunsch II, D.C.3
  • 48
    • 34249016393 scopus 로고    scopus 로고
    • Solving pseudomonotone variational inequalities and pseudoconvex optimization problems using the projection neural network
    • X. Hu and J. Wang. Solving pseudomonotone variational inequalities and pseudoconvex optimization problems using the projection neural network. IEEE Transactions on Neural Networks, 17(6):1487-1499, 2006.
    • (2006) IEEE Transactions On Neural Networks , vol.17 , Issue.6 , pp. 1487-1499
    • Hu, X.1    Wang, J.2
  • 49
    • 35148819444 scopus 로고    scopus 로고
    • Solving generally constrained generalized linear variational inequalities using the general projection neural networks
    • X. Hu and J. Wang. Solving generally constrained generalized linear variational inequalities using the general projection neural networks. IEEE Transactions on Neural Networks, 18(6):1697-1708, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.6 , pp. 1697-1708
    • Hu, X.1    Wang, J.2
  • 50
    • 57749106175 scopus 로고    scopus 로고
    • An improved dual neural network for solving a class of quadratic programming problems and its k-winners-take-all application
    • X. Hu and J. Wang. An improved dual neural network for solving a class of quadratic programming problems and its k-winners-take-all application. IEEE Tran. on Neural Networks, 19(12):2022-2031, 2008.
    • (2008) IEEE Tran. On Neural Networks , vol.19 , Issue.12 , pp. 2022-2031
    • Hu, X.1    Wang, J.2
  • 51
    • 34247515220 scopus 로고    scopus 로고
    • Tonically driven and self-sustaining activity in the lamprey hemicord: When can they co-exist?
    • M. Huss and M. Rehn. Tonically driven and self-sustaining activity in the lamprey hemicord: When can they co-exist? Neurocomputing, 70(10-12):1882-1886, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.10-12 , pp. 1882-1886
    • Huss, M.1    Rehn, M.2
  • 52
    • 33646102905 scopus 로고    scopus 로고
    • A model to explain the emergence of reward expectancy neurons using reinforcement learning and neural network
    • S. Ishii, M. Shidara, and K. Shibata. A model to explain the emergence of reward expectancy neurons using reinforcement learning and neural network. Neurocomputing, 69(10-12):1327-1331, 2006.
    • (2006) Neurocomputing , vol.69 , Issue.10-12 , pp. 1327-1331
    • Ishii, S.1    Shidara, M.2    Shibata, K.3
  • 53
    • 33746679374 scopus 로고    scopus 로고
    • Dynamic and interactive generation of object handling behaviors by a small humanoid robot using a dynamic neural network model
    • M. Ito, K. Noda, Y. Hoshino, and J. Tani. Dynamic and interactive generation of object handling behaviors by a small humanoid robot using a dynamic neural network model. Neural Networks, 19(3):323-337, 2006.
    • (2006) Neural Networks , vol.19 , Issue.3 , pp. 323-337
    • Ito, M.1    Noda, K.2    Hoshino, Y.3    Tani, J.4
  • 54
    • 33748305559 scopus 로고    scopus 로고
    • The crystallizing substochastic sequential machine extractor: CrySSMEx
    • H. Jacobsson. The crystallizing substochastic sequential machine extractor: CrySSMEx. Neural Computation, 18(9):2211-2255, 2006.
    • (2006) Neural Computation , vol.18 , Issue.9 , pp. 2211-2255
    • Jacobsson, H.1
  • 57
    • 1842421269 scopus 로고    scopus 로고
    • Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless telecommunication
    • H. Jaeger and H. Haas. Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless telecommunication. Science, 308:78-80, 2004.
    • (2004) Science , vol.308 , pp. 78-80
    • Jaeger, H.1    Haas, H.2
  • 58
    • 34249938474 scopus 로고    scopus 로고
    • Optimization and applications of Echo State Networks with leaky-integrator neurons
    • H. Jaeger, M. Lukosevicius, D. Popovici, and U. Siewert. Optimization and applications of Echo State Networks with leaky-integrator neurons. Neural Networks, 20(3):335-352, 2007.
    • (2007) Neural Networks , vol.20 , Issue.3 , pp. 335-352
    • Jaeger, H.1    Lukosevicius, M.2    Popovici, D.3    Siewert, U.4
  • 59
    • 35649011886 scopus 로고    scopus 로고
    • Birdsong recognition using prediction-based recurrent neural fuzzy networks
    • C. Juang and T. Chen. Birdsong recognition using prediction-based recurrent neural fuzzy networks. Neurocomputing, 71(1-3):121-130, 2007.
    • (2007) Neurocomputing , vol.71 , Issue.1-3 , pp. 121-130
    • Juang, C.1    Chen, T.2
  • 60
    • 34248650996 scopus 로고    scopus 로고
    • Hierarchical singleton-type recurrent neural fuzzy networks for noisy speech recognition
    • C. Juang, C. Chiou, and C. Lai. Hierarchical singleton-type recurrent neural fuzzy networks for noisy speech recognition. IEEE Transactions on Neural Networks, 18(3):833-843, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.3 , pp. 833-843
    • Juang, C.1    Chiou, C.2    Lai, C.3
  • 61
    • 34548151841 scopus 로고    scopus 로고
    • Recurrent fuzzy network design using hybrid evolutionary learning algorithms
    • C. Juang and I.-F. Chung. Recurrent fuzzy network design using hybrid evolutionary learning algorithms. Neurocomputing, 70(16-18):3001-3010, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.16-18 , pp. 3001-3010
    • Juang, C.1    Chung, I.-F.2
  • 62
    • 33750355517 scopus 로고    scopus 로고
    • Mold temperature control of a rubber injection-molding machine by TSK-type recurrent neural fuzzy network
    • C. Juang, S. Huang, and F. Duh. Mold temperature control of a rubber injection-molding machine by TSK-type recurrent neural fuzzy network. Neurocomputing, 70(1-3):559-567, 2006.
    • (2006) Neurocomputing , vol.70 , Issue.1-3 , pp. 559-567
    • Juang, C.1    Huang, S.2    Duh, F.3
  • 63
    • 40649116624 scopus 로고    scopus 로고
    • Reversed and forward buffering of behavioral spike sequences enables retrospective and prospective retrieval in hippocampal regions CA3 and CA1
    • R. A. Koene and M. E. Hasselmo. Reversed and forward buffering of behavioral spike sequences enables retrospective and prospective retrieval in hippocampal regions CA3 and CA1. Neural Networks, 21(2-3):276-288, 2008.
    • (2008) Neural Networks , vol.21 , Issue.2-3 , pp. 276-288
    • Koene, R.A.1    Hasselmo, M.E.2
  • 64
    • 49649113404 scopus 로고    scopus 로고
    • A new approach to knowledge-based design of recurrent neural networks
    • E. Kolman and M. Margaliot. A new approach to knowledge-based design of recurrent neural networks. IEEE Transactions on Neural Networks, 19(8):1389-1401, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.8 , pp. 1389-1401
    • Kolman, E.1    Margaliot, M.2
  • 65
    • 34247482711 scopus 로고    scopus 로고
    • Emergence of population synchrony in a layered network of the cat visual cortex
    • J. Kremkow, A. Kumar, S. Rotter, and A. Aertsen. Emergence of population synchrony in a layered network of the cat visual cortex. Neurocomputing, 70(10-12):2069-2073, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.10-12 , pp. 2069-2073
    • Kremkow, J.1    Kumar, A.2    Rotter, S.3    Aertsen, A.4
  • 68
    • 34248650742 scopus 로고    scopus 로고
    • A hybrid neurogenetic approach for stock forecasting
    • Y. Kwon and B. Moon. A hybrid neurogenetic approach for stock forecasting. IEEE Transactions on Neural Networks, 18(3):851-864, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.3 , pp. 851-864
    • Kwon, Y.1    Moon, B.2
  • 69
    • 34249775479 scopus 로고    scopus 로고
    • Fading memory and time series prediction in recurrent networks with different forms of plasticity
    • A. Lazar, G. Pipa, and J. Triesch. Fading memory and time series prediction in recurrent networks with different forms of plasticity. Neural Networks, 20(3):312-322, 2007.
    • (2007) Neural Networks , vol.20 , Issue.3 , pp. 312-322
    • Lazar, A.1    Pipa, G.2    Triesch, J.3
  • 70
    • 38649104174 scopus 로고    scopus 로고
    • A clustering-based approach for inferring recurrent neural networks as gene regulatory networks
    • W. Lee and K. Yang. A clustering-based approach for inferring recurrent neural networks as gene regulatory networks. Neurocomputing, 71(4-6):600-610, 2008.
    • (2008) Neurocomputing , vol.71 , Issue.4-6 , pp. 600-610
    • Lee, W.1    Yang, K.2
  • 71
    • 33645721789 scopus 로고    scopus 로고
    • Memory capacity for sequences in a recurrent network with biological constraints
    • C. Leibold and R. Kempter. Memory capacity for sequences in a recurrent network with biological constraints. Neural Computation, 18(4):904-941, 2006.
    • (2006) Neural Computation , vol.18 , Issue.4 , pp. 904-941
    • Leibold, C.1    Kempter, R.2
  • 72
    • 34247465951 scopus 로고    scopus 로고
    • Criticality of avalanche dynamics in adaptive recurrent networks
    • A. Levina, U. Ernst, and J. Michael Herrmann. Criticality of avalanche dynamics in adaptive recurrent networks. Neurocomputing, 70(10-12):1877-1881, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.10-12 , pp. 1877-1881
    • Levina, A.1    Ernst, U.2    Herrmann, J.M.3
  • 73
    • 33745184902 scopus 로고    scopus 로고
    • Stability in static delayed neural networks: A nonlinear measure approach
    • P. Li and J. Cao. Stability in static delayed neural networks: A nonlinear measure approach. Neurocomputing, 69(13-15):1776-1781, 2006.
    • (2006) Neurocomputing , vol.69 , Issue.13-15 , pp. 1776-1781
    • Li, P.1    Cao, J.2
  • 74
    • 35648996356 scopus 로고    scopus 로고
    • Exponential state estimation for recurrent neural networks with distributed delays
    • T. Li and S. Fei. Exponential state estimation for recurrent neural networks with distributed delays. Neurocomputing, 71(1-3):428-438, 2007.
    • (2007) Neurocomputing , vol.71 , Issue.1-3 , pp. 428-438
    • Li, T.1    Fei, S.2
  • 75
    • 38649092028 scopus 로고    scopus 로고
    • Positive invariant and global exponential attractive sets of neural networks with time-varying delays
    • X. Liao, Q. Luo, and Z. Zeng. Positive invariant and global exponential attractive sets of neural networks with time-varying delays. Neurocomputing, 71(4-6):513-518, 2008.
    • (2008) Neurocomputing , vol.71 , Issue.4-6 , pp. 513-518
    • Liao, X.1    Luo, Q.2    Zeng, Z.3
  • 76
    • 34248630846 scopus 로고    scopus 로고
    • RCMAC hybrid control for MIMO uncertain nonlinear systems using sliding-mode technology
    • C. Lin, L. Chen, and C. Chen. RCMAC hybrid control for MIMO uncertain nonlinear systems using sliding-mode technology. IEEE Transactions on Neural Networks, 18(3):708-720, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.3 , pp. 708-720
    • Lin, C.1    Chen, L.2    Chen, C.3
  • 77
    • 34548687453 scopus 로고    scopus 로고
    • Delayed standard neural network models for control systems
    • M. Liu. Delayed standard neural network models for control systems. IEEE Transactions on Neural Networks, 18(5):1376-1391, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.5 , pp. 1376-1391
    • Liu, M.1
  • 78
    • 34548658812 scopus 로고    scopus 로고
    • Discrete-time analogs for a class of continuous-time recurrent neural networks
    • P. Liu and Q. Han. Discrete-time analogs for a class of continuous-time recurrent neural networks. IEEE Transactions on Neural Networks, 18(5):1343-1355, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.5 , pp. 1343-1355
    • Liu, P.1    Han, Q.2
  • 79
    • 43449132396 scopus 로고    scopus 로고
    • A one-layer recurrent neural network with a discontinuous activation function for linear programming
    • Q. Liu and J. Wang. A one-layer recurrent neural network with a discontinuous activation function for linear programming. Neural Computation, 20(5):1366-1383, 2008.
    • (2008) Neural Computation , vol.20 , Issue.5 , pp. 1366-1383
    • Liu, Q.1    Wang, J.2
  • 80
    • 42549152732 scopus 로고    scopus 로고
    • A one-layer recurrent neural network with a discontinuous hardlimiting activation function for quadratic programming
    • Q. Liu and J. Wang. A one-layer recurrent neural network with a discontinuous hardlimiting activation function for quadratic programming. IEEE Transactions on Neural Networks, 19(4):558-570, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.4 , pp. 558-570
    • Liu, Q.1    Wang, J.2
  • 81
    • 40649091560 scopus 로고    scopus 로고
    • Two k-winners-take-all networks with discontinuous activation functions
    • Q. Liu and J. Wang. Two k-winners-take-all networks with discontinuous activation functions. Neural Networks, 21(2-3):406-413, 2008.
    • (2008) Neural Networks , vol.21 , Issue.2-3 , pp. 406-413
    • Liu, Q.1    Wang, J.2
  • 82
    • 34548629454 scopus 로고    scopus 로고
    • A simplified dual neural network for quadratic programming with its KWTA application
    • S. Liu and J. Wang. A simplified dual neural network for quadratic programming with its KWTA application. IEEE Transactions on Neural Networks, 17(6):1500-1510, 2006.
    • (2006) IEEE Transactions On Neural Networks , vol.17 , Issue.6 , pp. 1500-1510
    • Liu, S.1    Wang, J.2
  • 83
    • 55949130860 scopus 로고    scopus 로고
    • Development of a new EDRNN procedure in control of human arm trajectories
    • S. Liu, Y. Wang, and Q. Zhu. Development of a new EDRNN procedure in control of human arm trajectories. Neurocomputing, 72(1-3):490-499, 2008.
    • (2008) Neurocomputing , vol.72 , Issue.1-3 , pp. 490-499
    • Liu, S.1    Wang, Y.2    Zhu, Q.3
  • 84
    • 33646511197 scopus 로고    scopus 로고
    • Global exponential stability of generalized recurrent neural networks with discrete and distributed delays
    • Y. Liu, Z. Wang, and X. Liu. Global exponential stability of generalized recurrent neural networks with discrete and distributed delays. Neural Networks, 19(5):667-675, 2006.
    • (2006) Neural Networks , vol.19 , Issue.5 , pp. 667-675
    • Liu, Y.1    Wang, Z.2    Liu, X.3
  • 85
    • 54549105599 scopus 로고    scopus 로고
    • A fast and scalable recurrent neural network based on stochastic meta descent
    • Z. Liu and I. Elhanany. A fast and scalable recurrent neural network based on stochastic meta descent. IEEE Trans. on Neural Networks, 19(9):1651-1657, 2008.
    • (2008) IEEE Trans. On Neural Networks , vol.19 , Issue.9 , pp. 1651-1657
    • Liu, Z.1    Elhanany, I.2
  • 86
    • 42549156992 scopus 로고    scopus 로고
    • Delay-dependent criteria for global robust periodicity of uncertain switched recurrent neural networks with time-varying delay
    • X. Lou and B. Cui. Delay-dependent criteria for global robust periodicity of uncertain switched recurrent neural networks with time-varying delay. IEEE Transactions on Neural Networks, 19(4):549-557, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.4 , pp. 549-557
    • Lou, X.1    Cui, B.2
  • 88
    • 0036834701 scopus 로고    scopus 로고
    • Real-time computing without stable states: A new framework for neural computation based on perturbations
    • W. Maass, T. Natschläger, and H. Markram. Real-time computing without stable states: A new framework for neural computation based on perturbations. Neural Computation, 14(11):2531-2560, 2002.
    • (2002) Neural Computation , vol.14 , Issue.11 , pp. 2531-2560
    • Maass, W.1    Natschläger, T.2    Markram, H.3
  • 89
    • 33846074352 scopus 로고    scopus 로고
    • Dynamics of winner-take-all competition in recurrent neural networks with lateral inhibition
    • Z. Mao and S. G. Massaquoi. Dynamics of winner-take-all competition in recurrent neural networks with lateral inhibition. IEEE Transactions on Neural Networks, 18(1):55-69, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.1 , pp. 55-69
    • Mao, Z.1    Massaquoi, S.G.2
  • 90
    • 38649094876 scopus 로고    scopus 로고
    • Parametric improvement of lateral interaction in accumulative computation in motion-based segmentation
    • J. Martinez-Cantos, E. Carmona, A. Fernandez-Caballero, and M. T. Lopez. Parametric improvement of lateral interaction in accumulative computation in motion-based segmentation. Neurocomputing, 71(4-6):776-786, 2008.
    • (2008) Neurocomputing , vol.71 , Issue.4-6 , pp. 776-786
    • Martinez-Cantos, J.1    Carmona, E.2    Fernandez-Caballero, A.3    Lopez, M.T.4
  • 91
    • 34247571107 scopus 로고    scopus 로고
    • Modelling adaptation aftereffects in associative memory
    • F. Menghini, N. van Rijsbergen, and A. Treves. Modelling adaptation aftereffects in associative memory. Neurocomputing, 70(10-12):2000-2004, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.10-12 , pp. 2000-2004
    • Menghini, F.1    van Rijsbergen, N.2    Treves, A.3
  • 92
    • 55749106907 scopus 로고    scopus 로고
    • Exact solutions for rate and synchrony in recurrent networks of coincidence detectors
    • S. Mikula and E. Niebur. Exact solutions for rate and synchrony in recurrent networks of coincidence detectors. Neural Computation, 20(11):2637-2661, 2008.
    • (2008) Neural Computation , vol.20 , Issue.11 , pp. 2637-2661
    • Mikula, S.1    Niebur, E.2
  • 93
    • 34447279459 scopus 로고    scopus 로고
    • Selectivity and stability via dendritic nonlinearity
    • K. Morita, M. Okada, and K. Aihara. Selectivity and stability via dendritic nonlinearity. Neural Computation, 19(7):1798-1853, 2007.
    • (2007) Neural Computation , vol.19 , Issue.7 , pp. 1798-1853
    • Morita, K.1    Okada, M.2    Aihara, K.3
  • 95
    • 56949101180 scopus 로고    scopus 로고
    • A model for learning to segment temporal sequences, utilizing a mixture of RNN experts together with adaptive variance
    • J. Namikawa and J. Tani. A model for learning to segment temporal sequences, utilizing a mixture of RNN experts together with adaptive variance. Neural Networks, 21(10):1466-1475, 2008.
    • (2008) Neural Networks , vol.21 , Issue.10 , pp. 1466-1475
    • Namikawa, J.1    Tani, J.2
  • 96
    • 51349131136 scopus 로고    scopus 로고
    • Encoding and decoding spikes for dynamic stimuli
    • R. Natarajan, Q. J. M. Huys, P. Dayan, and R. S. Zemel. Encoding and decoding spikes for dynamic stimuli. Neural Computation, 20(9):2325-2360, 2008.
    • (2008) Neural Computation , vol.20 , Issue.9 , pp. 2325-2360
    • Natarajan, R.1    Huys, Q.J.M.2    Dayan, P.3    Zemel, R.S.4
  • 97
    • 53349178774 scopus 로고    scopus 로고
    • Neural integrator: A sandpile model
    • M. Nikitchenko and A. Koulakov. Neural integrator: A sandpile model. Neural Computation, 20(10):2379-2417, 2008.
    • (2008) Neural Computation , vol.20 , Issue.10 , pp. 2379-2417
    • Nikitchenko, M.1    Koulakov, A.2
  • 98
    • 34249717976 scopus 로고    scopus 로고
    • Recurrent network simulations of two types of non-concentric retinal ganglion cells
    • W. Niu and J. Yuan. Recurrent network simulations of two types of non-concentric retinal ganglion cells. Neurocomputing, 70(13-15):2576-2580, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.13-15 , pp. 2576-2580
    • Niu, W.1    Yuan, J.2
  • 99
    • 33749041444 scopus 로고    scopus 로고
    • Recurrent neural network architecture with pre-synaptic inhibition for incremental learning
    • H. Ohta and Y. P. Gunji. Recurrent neural network architecture with pre-synaptic inhibition for incremental learning. Neural Networks, 19(8):1106-1119, 2006.
    • (2006) Neural Networks , vol.19 , Issue.8 , pp. 1106-1119
    • Ohta, H.1    Gunji, Y.P.2
  • 100
    • 34249907849 scopus 로고    scopus 로고
    • Recurrent neural network modeling of nearshore sandbar behavior
    • L. Pape, B. G. Ruessink, M. A. Wiering, and I. L. Turner. Recurrent neural network modeling of nearshore sandbar behavior. Neural Networks, 20(4):509-518, 2007.
    • (2007) Neural Networks , vol.20 , Issue.4 , pp. 509-518
    • Pape, L.1    Ruessink, B.G.2    Wiering, M.A.3    Turner, I.L.4
  • 102
    • 45749090054 scopus 로고    scopus 로고
    • Solving the problem of negative synaptic weights in cortical models
    • C. Parisien, C. H. Anderson, and C. Eliasmith. Solving the problem of negative synaptic weights in cortical models. Neural Computation, 20(6):1473-1494, 2008.
    • (2008) Neural Computation , vol.20 , Issue.6 , pp. 1473-1494
    • Parisien, C.1    Anderson, C.H.2    Eliasmith, C.3
  • 103
    • 34248662730 scopus 로고    scopus 로고
    • Stability analysis and the stabilization of a class of discrete-time dynamic neural networks
    • K. Patan. Stability analysis and the stabilization of a class of discrete-time dynamic neural networks. IEEE Transactions on Neural Networks, 18(3):660-673, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.3 , pp. 660-673
    • Patan, K.1
  • 104
    • 34548148985 scopus 로고    scopus 로고
    • Adaptive recurrent cerebellar model articulation controller for linear ultrasonic motor with optimal learning rates
    • Y. Peng and C. Lin. Adaptive recurrent cerebellar model articulation controller for linear ultrasonic motor with optimal learning rates. Neurocomputing, 70(16-18):2626-2637, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.16-18 , pp. 2626-2637
    • Peng, Y.1    Lin, C.2
  • 105
    • 33746873249 scopus 로고    scopus 로고
    • Analog neural network for support vector machine learning
    • R. Perfetti and E. Ricci. Analog neural network for support vector machine learning. IEEE Transactions on Neural Networks, 17(4):1085-1091, 2006.
    • (2006) IEEE Transactions On Neural Networks , vol.17 , Issue.4 , pp. 1085-1091
    • Perfetti, R.1    Ricci, E.2
  • 106
    • 56949101943 scopus 로고    scopus 로고
    • Spontaneous scale-free structure of spike flow graphs in recurrent neural networks
    • F. Piekniewski and T. Schreiber. Spontaneous scale-free structure of spike flow graphs in recurrent neural networks. Neural Networks, 21(10):1530-1536, 2008.
    • (2008) Neural Networks , vol.21 , Issue.10 , pp. 1530-1536
    • Piekniewski, F.1    Schreiber, T.2
  • 107
    • 40649090599 scopus 로고    scopus 로고
    • Dynamical model of salience gated working memory, action selection and reinforcement based on basal ganglia and dopamine feedback
    • A. Ponzi. Dynamical model of salience gated working memory, action selection and reinforcement based on basal ganglia and dopamine feedback. Neural Networks, 21(2-3):322-330, 2008.
    • (2008) Neural Networks , vol.21 , Issue.2-3 , pp. 322-330
    • Ponzi, A.1
  • 108
    • 34547129948 scopus 로고    scopus 로고
    • Training recurrent neurocontrollers for robustness with derivative-free Kalman filter
    • D. V. Prokhorov. Training recurrent neurocontrollers for robustness with derivative-free Kalman filter. IEEE Transactions on Neural Networks, 17(6):1606-1616, 2006.
    • (2006) IEEE Transactions On Neural Networks , vol.17 , Issue.6 , pp. 1606-1616
    • Prokhorov, D.V.1
  • 109
    • 34547133026 scopus 로고    scopus 로고
    • Training recurrent neurocontrollers for real-time applications
    • D. V. Prokhorov. Training recurrent neurocontrollers for real-time applications. IEEE Transactions on Neural Networks, 18(4):1003-1015, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.4 , pp. 1003-1015
    • Prokhorov, D.V.1
  • 110
    • 40649102371 scopus 로고    scopus 로고
    • Toyota Prius HEV neurocontrol and diagnostics
    • D. V. Prokhorov. Toyota Prius HEV neurocontrol and diagnostics. Neural Networks, 21(2-3):458-465, 2008.
    • (2008) Neural Networks , vol.21 , Issue.2-3 , pp. 458-465
    • Prokhorov, D.V.1
  • 111
    • 55949121875 scopus 로고    scopus 로고
    • Switching analysis of 2-D neural networks with nonsaturating linear threshold transfer functions
    • H. Qu, Z. Yi, and X. Wang. Switching analysis of 2-D neural networks with nonsaturating linear threshold transfer functions. Neurocomputing, 72(1-3):413-419, 2008.
    • (2008) Neurocomputing , vol.72 , Issue.1-3 , pp. 413-419
    • Qu, H.1    Yi, Z.2    Wang, X.3
  • 112
    • 53849116116 scopus 로고    scopus 로고
    • Recurrent neural associative learning of forward and inverse kinematics for movement generation of the redundant pa-10 robot
    • F. R. Reinhart and J. J. Steil. Recurrent neural associative learning of forward and inverse kinematics for movement generation of the redundant pa-10 robot. In Proc. LAB-RS, volume 1, pages 35-40, 2008.
    • (2008) Proc. LAB-RS , vol.1 , pp. 35-40
    • Reinhart, F.R.1    Steil, J.J.2
  • 114
    • 33845992188 scopus 로고    scopus 로고
    • Mean-driven and fluctuationdriven persistent activity in recurrent networks
    • A. Renart, R. Moreno-Bote, X. Wang, and N. Parga. Mean-driven and fluctuationdriven persistent activity in recurrent networks. Neural Computation, 19(1):1-46, 2007.
    • (2007) Neural Computation , vol.19 , Issue.1 , pp. 1-46
    • Renart, A.1    Moreno-Bote, R.2    Wang, X.3    Parga, N.4
  • 116
    • 33749050766 scopus 로고    scopus 로고
    • Computational algorithms and neuronal network models underlying decision processes
    • Y. Sakai, H. Okamoto, and T. Fukai. Computational algorithms and neuronal network models underlying decision processes. Neural Networks, 19(8):1091-1105, 2006.
    • (2006) Neural Networks , vol.19 , Issue.8 , pp. 1091-1105
    • Sakai, Y.1    Okamoto, H.2    Fukai, T.3
  • 118
    • 84858767465 scopus 로고    scopus 로고
    • On computational power and the orderchaos phase transition in reservoir computing
    • B. Schrauwen, L. Buesing, and R. Legenstein. On computational power and the orderchaos phase transition in reservoir computing. In Proceedings of NIPS 2008, 2009.
    • (2009) Proceedings of NIPS 2008
    • Schrauwen, B.1    Buesing, L.2    Legenstein, R.3
  • 119
    • 40649092298 scopus 로고    scopus 로고
    • Compact hardware Liquid State Machines on FPGA for real-time speech recognition
    • B. Schrauwen, M. D'Haene, D. Verstraeten, and J. V. Campenhout. Compact hardware Liquid State Machines on FPGA for real-time speech recognition. Neural Networks, 21(2-3):511-523, 2008.
    • (2008) Neural Networks , vol.21 , Issue.2-3 , pp. 511-523
    • Schrauwen, B.1    D'Haene, M.2    Verstraeten, D.3    Campenhout, J.V.4
  • 121
    • 52149090973 scopus 로고    scopus 로고
    • Delay-dependent stability for recurrent neural networks with time-varying delays
    • H. Shao. Delay-dependent stability for recurrent neural networks with time-varying delays. IEEE Transactions on Neural Networks, 19(9):1647-1651, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.9 , pp. 1647-1651
    • Shao, H.1
  • 122
    • 38149136549 scopus 로고    scopus 로고
    • Noise-induced stabilization of the recurrent neural networks with mixed time-varying delays and Markovian-switching parameters
    • Y. Shen and J. Wang. Noise-induced stabilization of the recurrent neural networks with mixed time-varying delays and Markovian-switching parameters. IEEE Transactions on Neural Networks, 18(6):1857-1862, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.6 , pp. 1857-1862
    • Shen, Y.1    Wang, J.2
  • 123
    • 40949138432 scopus 로고    scopus 로고
    • An improved algebraic criterion for global exponential stability of recurrent neural networks with time-varying delays
    • Y. Shen and J. Wang. An improved algebraic criterion for global exponential stability of recurrent neural networks with time-varying delays. IEEE Transactions on Neural Networks, 19(3):528-531, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.3 , pp. 528-531
    • Shen, Y.1    Wang, J.2
  • 124
    • 34047166022 scopus 로고    scopus 로고
    • Support vector echo-state machine for chaotic time-series prediction
    • Z. Shi and M. Han. Support vector echo-state machine for chaotic time-series prediction. IEEE Transactions on Neural Networks, 18(2):359-372, 2007.
    • (2007) IEEE Transactions On Neural Networks , vol.18 , Issue.2 , pp. 359-372
    • Shi, Z.1    Han, M.2
  • 125
    • 33845971904 scopus 로고    scopus 로고
    • A new approach to solve the traveling salesman problem
    • P. H. Siqueira, M. T. A. Steiner, and S. Scheer. A new approach to solve the traveling salesman problem. Neurocomputing, 70(4-6):1013-1021, 2007.
    • (2007) Neurocomputing , vol.70 , Issue.4-6 , pp. 1013-1021
    • Siqueira, P.H.1    Steiner, M.T.A.2    Scheer, S.3
  • 126
    • 56449106923 scopus 로고    scopus 로고
    • Exponential stability of recurrent neural networks with both time-varying delays and general activation functions via LMI approach
    • Q. Song. Exponential stability of recurrent neural networks with both time-varying delays and general activation functions via LMI approach. Neurocomputing, 71(13-15):2823-2830, 2008.
    • (2008) Neurocomputing , vol.71 , Issue.13-15 , pp. 2823-2830
    • Song, Q.1
  • 127
    • 56449088476 scopus 로고    scopus 로고
    • Robust adaptive gradient-descent training algorithm for recurrent neural networks in discrete time domain
    • Q. Song, Y. Wu, and Y. C. Soh. Robust adaptive gradient-descent training algorithm for recurrent neural networks in discrete time domain. IEEE Trans. on Neural Networks, 19(11):1841-1853, 2008.
    • (2008) IEEE Trans. On Neural Networks , vol.19 , Issue.11 , pp. 1841-1853
    • Song, Q.1    Wu, Y.2    Soh, Y.C.3
  • 130
    • 32544455147 scopus 로고    scopus 로고
    • Online stability of backpropagation-decorrelation recurrent learning
    • SPEC. ISSUE
    • J. J. Steil. Online stability of backpropagation-decorrelation recurrent learning. Neurocomputing, 69(7-9 SPEC. ISS.):642-650, 2006.
    • (2006) Neurocomputing , vol.69 , Issue.7-9 , pp. 642-650
    • Steil, J.J.1
  • 131
    • 0033640676 scopus 로고    scopus 로고
    • Robust local stability of multilayer recurrent neural networks
    • J. A. K. Suykens, B. D. Moor, and J. Vandewalle. Robust local stability of multilayer recurrent neural networks. IEEE Trans. Neural Networks, 11(1):222-229, 2000.
    • (2000) IEEE Trans. Neural Networks , vol.11 , Issue.1 , pp. 222-229
    • Suykens, J.A.K.1    Moor, B.D.2    Vandewalle, J.3
  • 132
    • 33750973390 scopus 로고    scopus 로고
    • PIRANHA: Policy iteration for recurrent artificial neural networks with hidden activities
    • I. Szita and A. Lorincz. PIRANHA: Policy iteration for recurrent artificial neural networks with hidden activities. Neurocomputing, 70(1-3):577-591, 2006.
    • (2006) Neurocomputing , vol.70 , Issue.1-3 , pp. 577-591
    • Szita, I.1    Lorincz, A.2
  • 133
    • 33644895011 scopus 로고    scopus 로고
    • Dynamics analysis and analog associative memory of networks with LT neurons
    • H. Tang, K. C. Tan, and E. J. Teoh. Dynamics analysis and analog associative memory of networks with LT neurons. IEEE Transactions on Neural Networks, 17(2):409-418, 2006.
    • (2006) IEEE Transactions On Neural Networks , vol.17 , Issue.2 , pp. 409-418
    • Tang, H.1    Tan, K.C.2    Teoh, E.J.3
  • 134
    • 40649126353 scopus 로고    scopus 로고
    • An asynchronous recurrent linear threshold network approach to solving the traveling salesman problem
    • E. J. Teoh, K. C. Tan, H. J. Tang, C. Xiang, and C. K. Goh. An asynchronous recurrent linear threshold network approach to solving the traveling salesman problem. Neurocomputing, 71(7-9):1359-1372, 2008.
    • (2008) Neurocomputing , vol.71 , Issue.7-9 , pp. 1359-1372
    • Teoh, E.J.1    Tan, K.C.2    Tang, H.J.3    Xiang, C.4    Goh, C.K.5
  • 136
    • 33645701621 scopus 로고    scopus 로고
    • Learning beyond finite memory in recurrent networks of spiking neurons
    • P. Tino and A. J. S. Mills. Learning beyond finite memory in recurrent networks of spiking neurons. Neural Computation, 18(3):591-613, 2006.
    • (2006) Neural Computation , vol.18 , Issue.3 , pp. 591-613
    • Tino, P.1    Mills, A.J.S.2
  • 138
    • 53349180261 scopus 로고    scopus 로고
    • Adaptive classification of temporal signals in fixed-weight recurrent neural networks: An existence proof
    • I. Y. Tyukin, D. Prokhorov, and C. Van Leeuwen. Adaptive classification of temporal signals in fixed-weight recurrent neural networks: An existence proof. Neural Computation, 20(10):2564-2596, 2008.
    • (2008) Neural Computation , vol.20 , Issue.10 , pp. 2564-2596
    • Tyukin, I.Y.1    Prokhorov, D.2    van Leeuwen, C.3
  • 139
    • 47049111446 scopus 로고    scopus 로고
    • Adaptive integration in the visual cortex by depressing recurrent cortical circuits
    • M. C. W. Van Rossum, M. A. A. Van Der Meer, D. Xiao, and M. W. Oram. Adaptive integration in the visual cortex by depressing recurrent cortical circuits. Neural Computation, 20(7):1847-1872, 2008.
    • (2008) Neural Computation , vol.20 , Issue.7 , pp. 1847-1872
    • van Rossum, M.C.W.1    van der Meer, M.A.A.2    Xiao, D.3    Oram, M.W.4
  • 141
    • 34249776914 scopus 로고    scopus 로고
    • Online design of an Echo State Network based wide area monitor for a multimachine power system
    • G. K. Venayagamoorthy. Online design of an Echo State Network based wide area monitor for a multimachine power system. Neural Networks, 20(3):404-413, 2007.
    • (2007) Neural Networks , vol.20 , Issue.3 , pp. 404-413
    • Venayagamoorthy, G.K.1
  • 142
  • 144
    • 33746867472 scopus 로고    scopus 로고
    • Learning lateral interactions for feature binding and sensory segmentation from prototypic basis interactions
    • S. Weng, H. Wersing, J. J. Steil, and H. Ritter. Learning lateral interactions for feature binding and sensory segmentation from prototypic basis interactions. IEEE Transactions on Neural Networks, 17(4):843-862, 2006.
    • (2006) IEEE Transactions On Neural Networks , vol.17 , Issue.4 , pp. 843-862
    • Weng, S.1    Wersing, H.2    Steil, J.J.3    Ritter, H.4
  • 145
    • 34447629704 scopus 로고    scopus 로고
    • A new neural network for solving nonlinear projection equations
    • Y. Xia and G. Feng. A new neural network for solving nonlinear projection equations. Neural Networks, 20(5):577-589, 2007.
    • (2007) Neural Networks , vol.20 , Issue.5 , pp. 577-589
    • Xia, Y.1    Feng, G.2
  • 146
    • 49649119936 scopus 로고    scopus 로고
    • A novel recurrent neural network for solving nonlinear optimization problems with inequality constraints
    • Y. Xia, G. Feng, and J. Wang. A novel recurrent neural network for solving nonlinear optimization problems with inequality constraints. IEEE Transactions on Neural Networks, 19(8):1340-1353, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.8 , pp. 1340-1353
    • Xia, Y.1    Feng, G.2    Wang, J.3
  • 147
    • 41549108133 scopus 로고    scopus 로고
    • A cooperative recurrent neural network for solving L1 estimation problems with general linear constraints
    • Y. Xia and M. S. Kamel. A cooperative recurrent neural network for solving L1 estimation problems with general linear constraints. Neural Computation, 20(3):844-872, 2008.
    • (2008) Neural Computation , vol.20 , Issue.3 , pp. 844-872
    • Xia, Y.1    Kamel, M.S.2
  • 148
    • 40749113212 scopus 로고    scopus 로고
    • An estimation of the domain of attraction for recurrent neural networks with time-varying delays
    • J. Xu, Y. Cao, D. Pi, and Y. Sun. An estimation of the domain of attraction for recurrent neural networks with time-varying delays. Neurocomputing, 71(7-9):1566-1577, 2008.
    • (2008) Neurocomputing , vol.71 , Issue.7-9 , pp. 1566-1577
    • Xu, J.1    Cao, Y.2    Pi, D.3    Sun, Y.4
  • 149
    • 34848893948 scopus 로고    scopus 로고
    • Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization
    • R. Xu, G. K. Venayagamoorthy, and D. C. Wunsch II. Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization. Neural Networks, 20(8):917-927, 2007.
    • (2007) Neural Networks , vol.20 , Issue.8 , pp. 917-927
    • Xu, R.1    Venayagamoorthy, G.K.2    Wunsch II, D.C.3
  • 151
    • 57149090913 scopus 로고    scopus 로고
    • Emergence of functional hierarchy in a multiple timescale neural network model: A humanoid robot experiment
    • Y. Yamashita and J. Tani. Emergence of functional hierarchy in a multiple timescale neural network model: a humanoid robot experiment. PLoS Computational Biology, 4(11), 2008.
    • (2008) PLoS Computational Biology , vol.4 , Issue.11
    • Yamashita, Y.1    Tani, J.2
  • 153
    • 40549096757 scopus 로고    scopus 로고
    • A normalized adaptive training of recurrent neural networks with augmented error gradient
    • W. Yilei, S. Qing, and L. Sheng. A normalized adaptive training of recurrent neural networks with augmented error gradient. IEEE Transactions on Neural Networks, 19(2):351-356, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.2 , pp. 351-356
    • Yilei, W.1    Qing, S.2    Sheng, L.3
  • 154
    • 54349106342 scopus 로고    scopus 로고
    • Adaptive output feedback control of flexible-joint robots using neural networks: Dynamic surface design approach
    • S. J. Yoo, J. B. Park, and Y. H. Choi. Adaptive output feedback control of flexible-joint robots using neural networks: Dynamic surface design approach. IEEE Transactions on Neural Networks, 19(10):1712-1726, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.10 , pp. 1712-1726
    • Yoo, S.J.1    Park, J.B.2    Choi, Y.H.3
  • 155
    • 33750311824 scopus 로고    scopus 로고
    • Multiple recurrent neural networks for stable adaptive control
    • W. Yu. Multiple recurrent neural networks for stable adaptive control. Neurocomputing, 70(1-3):430-444, 2006.
    • (2006) Neurocomputing , vol.70 , Issue.1-3 , pp. 430-444
    • Yu, W.1
  • 156
    • 44349132890 scopus 로고    scopus 로고
    • Stability and Hopf bifurcation of a general delayed recurrent neural network
    • W. Yu, J. Cao, and G. Chen. Stability and Hopf bifurcation of a general delayed recurrent neural network. IEEE Transactions on Neural Networks, 19(5):845-854, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.5 , pp. 845-854
    • Yu, W.1    Cao, J.2    Chen, G.3
  • 157
    • 33751212466 scopus 로고    scopus 로고
    • Global exponential stability of recurrent neural networks with timevarying delays in the presence of strong external stimuli
    • Z. Zeng and J. Wang. Global exponential stability of recurrent neural networks with timevarying delays in the presence of strong external stimuli. Neural Networks, 19(10):1528-1537, 2006.
    • (2006) Neural Networks , vol.19 , Issue.10 , pp. 1528-1537
    • Zeng, Z.1    Wang, J.2
  • 158
    • 33646523344 scopus 로고    scopus 로고
    • Improved conditions for global exponential stability of recurrent neural networks with time-varying delays
    • Z. Zeng and J. Wang. Improved conditions for global exponential stability of recurrent neural networks with time-varying delays. IEEE Transactions on Neural Networks, 17(3):623-635, 2006.
    • (2006) IEEE Transactions On Neural Networks , vol.17 , Issue.3 , pp. 623-635
    • Zeng, Z.1    Wang, J.2
  • 159
    • 34548011738 scopus 로고    scopus 로고
    • Analysis and design of associative memories based on recurrent neural networks with linear saturation activation functions and time-varying delays
    • Z. Zeng and J. Wang. Analysis and design of associative memories based on recurrent neural networks with linear saturation activation functions and time-varying delays. Neural Computation, 19(8):2149-2182, 2007.
    • (2007) Neural Computation , vol.19 , Issue.8 , pp. 2149-2182
    • Zeng, Z.1    Wang, J.2
  • 160
    • 55949113895 scopus 로고    scopus 로고
    • Improved delay-dependent exponential stability criteria for discrete-time recurrent neural networks with time-varying delays
    • B. Zhang, S. Xu, and Y. Zou. Improved delay-dependent exponential stability criteria for discrete-time recurrent neural networks with time-varying delays. Neurocomputing, 72(1-3):321-330, 2008.
    • (2008) Neurocomputing , vol.72 , Issue.1-3 , pp. 321-330
    • Zhang, B.1    Xu, S.2    Zou, Y.3
  • 161
    • 44349110244 scopus 로고    scopus 로고
    • Global asymptotic stability of recurrent neural networks with multiple time-varying delays
    • H. Zhang, Z. Wang, and D. Liu. Global asymptotic stability of recurrent neural networks with multiple time-varying delays. IEEE Trans. Neural Networks, 19(5):855-873, 2008.
    • (2008) IEEE Trans. Neural Networks , vol.19 , Issue.5 , pp. 855-873
    • Zhang, H.1    Wang, Z.2    Liu, D.3
  • 162
    • 39549123043 scopus 로고    scopus 로고
    • Multiperiodicity and attractivity of delayed recurrent neural networks with unsaturating piecewise linear transfer functions
    • L. Zhang, Z. Yi, and J. Yu. Multiperiodicity and attractivity of delayed recurrent neural networks with unsaturating piecewise linear transfer functions. IEEE Transactions on Neural Networks, 19(1):158-167, 2008.
    • (2008) IEEE Transactions On Neural Networks , vol.19 , Issue.1 , pp. 158-167
    • Zhang, L.1    Yi, Z.2    Yu, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.