Analysis of the dynamical behavior of a feedback auto-associative memory

Neurocomputing

Volumn 71, Issue 4-6, 2008, Pages 486-494

  Amiri, Mahmood ^a   Saeb, Sohrab ^a   Yazdanpanah, Mohammad Javad ^a   Seyyedsalehi, S Ali ^a  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Feedback auto associative memory; Fixed points; Stability analysis

Indexed keywords

COMPUTER SIMULATION; LINEAR STABILITY ANALYSIS; MULTILAYER NEURAL NETWORKS;

DYNAMICAL SYSTEM THEORY; FEEDBACK AUTO-ASSOCIATIVE MEMORY; SELF-FEEDBACK NEURAL NETWORK;

RECURRENT NEURAL NETWORKS;

ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; ASSOCIATIVE MEMORY; DYNAMICS; FEEDBACK SYSTEM; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; PERCEPTRON; PRIORITY JOURNAL; SIMULATION; THEORY;

EID: 38649123750     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2007.07.027     Document Type: Article

References (20)

1. Amari S.I. Learning patterns and pattern sequences by self-organizing nets. IEEE Trans. Comput. 21 11 (1972) 1197-1206
2. M. Amiri, M.B. Menhaj, A. Sadeghian, A simple and efficient training algorithm to store desired number of stable equilibrium points in self-feedback neural network structures, J. Comput. Inform. Syst., in press.
3. Atiya A., and Abu-Mostafa Y.S. An analog feedback associative memory. IEEE Trans. Neural Networks 2 (1993) 117-126
4. J. Cao, On the domain of attraction and convergence rate of Hopfield continuous feedback neural networks, in: Proceedings of the Third World Congress on Intelligent Control and Automation, Hefei, China, 2000, pp. 3277-3280.
5. Z.Y. Chen, M. Desai, Multiple-valued feedback neural networks for image restoration, in: Proceedings of the International Conference on Image Processing 1, Lausanne, Switzerland, 1996, pp. 753-756.
6. Cheng K.S., Lin J.S., and Mao C.W. The application of competitive Hopfield neural network to medical image segmentation. IEEE Trans. Med. Imag. 15 4 (1996) 560-567
7. O.K. Dekhtyarenko, D.O. Gorodnichy, High performance associative neural networks: overview and library, in: Proceedings of the Canadian Conference on Artificial Intelligence, Québec City, Québec, Canada, 2006.
8. A.M. Farahmand, M.J. Yazdanpanah, Channel assignment using chaotic simulated annealing enhanced Hopfield neural network, in: Proceedings of the IJCNN, Vancouver, Canada, 2006, pp. 4491-4497.
9. Hagan M.T., and Menhaj M.B. Training feedforward networks with the Marquardt algorithm. IEEE Trans. Neural Networks 5 (1994) 989-993
10. Haykin S. Neural Networks: A Comprehensive Foundation. second ed (1998), Prentice-Hall, Englewood Cliffs, NJ
11. Hopfield J.J. Neural networks and physical systems with emergent collective computational abilities. Acad. Sci. 79 (1982) 2554-2558
12. Jin L., and Gupta M. Equilibrium capacity of analog feedback neural networks. IEEE Trans. Neural Networks 7 (1996) 782-787
13. Ku C.C., and Lee K.Y. Diagonal recurrent neural network for dynamic system control. IEEE Trans. Neural Networks 6 (1995) 144-155
14. Kulenovic M.R.S., Kulenovic K.R.S., and Merino O. Discrete Dynamical Systems and Difference Equations with Mathematica (2002), Chapman & Hall/CRC pp. 20-37
15. Plett G.L. Adaptive inverse control of linear and nonlinear systems using dynamic neural networks. IEEE Trans. Neural Networks 14 (2003) 360-372
16. Reznik A., Galinskaya A., Dekhtyarenko O., and Nowicki D. Preprocessing of matrix qcm sensors data for the classification by means of neural network. Sensors Actuators B 106 (2005) 158-163
17. S. Saeb, M.B. Menhaj, S.A. Seyyedsalehi, A new evolution-based training method for dynamic synapse neural networks, in: Proceedings of the IASTED International Conference on Computational Intelligence (CI'06), San Francisco, USA, 2006, pp. 188-193.
18. Sperduti A. Stability properties of labeling recursive auto-associative memory. IEEE Trans. Neural Networks 6 (1995) 1452-1460
19. Sudharsanan S.I., and Sundareshan M.K. Equilibrium characterization of dynamical neural networks and a systematic synthesis procedure for associative memories. IEEE Trans. Neural Networks 2 (1991) 509-521
20. D. Veljkovic, D. Rakovic, Z. Durovic, S. Stankovic, The binary vectors storing procedure in an analog feedback associative memory, 5th Seminar on Neural Network Applications in Electrical Engineering, Belgrade, Yugoslavia, 2000, pp. 37-41.