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Volumn 16, Issue 6, 2008, Pages 1411-1424

A self-evolving interval type-2 fuzzy neural network with online structure and parameter learning

Author keywords

Evolving system; Fuzzy neural networks (FNNs); Online fuzzy clustering; Structure learning; Type 2 fuzzy systems

Indexed keywords

ACOUSTIC SIGNAL PROCESSING; CONTROL THEORY; EDUCATION; FUZZY CLUSTERING; FUZZY LOGIC; FUZZY RULES; FUZZY SETS; FUZZY SYSTEMS; KALMAN FILTERS; LEARNING ALGORITHMS; NEURAL NETWORKS; ONLINE SYSTEMS; SOLUTE TRANSPORT; SPURIOUS SIGNAL NOISE; VEGETATION;

EID: 58149487281     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/TFUZZ.2008.925907     Document Type: Article
Times cited : (299)

References (47)
  • 2
    • 0036530350 scopus 로고    scopus 로고
    • Type-2 fuzzy sets made simple
    • Apr
    • J. M. Mendel and R. I. John, "Type-2 fuzzy sets made simple," IEEE Trans. Fuzzy Syst., vol. 10, no. 2, pp. 117-127, Apr. 2002.
    • (2002) IEEE Trans. Fuzzy Syst , vol.10 , Issue.2 , pp. 117-127
    • Mendel, J.M.1    John, R.I.2
  • 4
    • 0034297774 scopus 로고    scopus 로고
    • Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters
    • Oct
    • Q. Liang and J. M. Mendel, "Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters," IEEE Trans. Fuzzy Syst., vol. 8, no. 5, pp. 551-563, Oct. 2000.
    • (2000) IEEE Trans. Fuzzy Syst , vol.8 , Issue.5 , pp. 551-563
    • Liang, Q.1    Mendel, J.M.2
  • 5
    • 13244265796 scopus 로고    scopus 로고
    • Pattern recognition using type-2 fuzzy sets
    • H. B. Mitchell, "Pattern recognition using type-2 fuzzy sets," Inf. Sci., vol. 170, pp. 409-418, 2005.
    • (2005) Inf. Sci , vol.170 , pp. 409-418
    • Mitchell, H.B.1
  • 6
    • 70349384855 scopus 로고    scopus 로고
    • Intelligent control of non-linear dynamic plants using type-2 fuzzy logic and neural networks
    • presented at the, Budapest, Hungary, Jul
    • P.Melin and O. Castillo, "Intelligent control of non-linear dynamic plants using type-2 fuzzy logic and neural networks," presented at the IEEE Int. Conf. Fuzzy Syst., Budapest, Hungary, Jul. 2004.
    • (2004) IEEE Int. Conf. Fuzzy Syst
    • Melin, P.1    Castillo, O.2
  • 7
    • 4344620181 scopus 로고    scopus 로고
    • A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots
    • Aug
    • H. Hagras, "A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots," IEEE Trans. Fuzzy Syst., vol. 12, no. 4, pp. 524-539, Aug. 2004.
    • (2004) IEEE Trans. Fuzzy Syst , vol.12 , Issue.4 , pp. 524-539
    • Hagras, H.1
  • 8
    • 2942670995 scopus 로고    scopus 로고
    • Hardware architecture and FPGA implementation of a type-2 fuzzy system
    • Boston, MA
    • M. Melgarejo and C. Pena-Reyes, "Hardware architecture and FPGA implementation of a type-2 fuzzy system," in Proc. Great Lakes Symp. VLSI (GLSVLSI), Boston, MA, 2004, pp. 458-261.
    • (2004) Proc. Great Lakes Symp. VLSI (GLSVLSI) , pp. 458-261
    • Melgarejo, M.1    Pena-Reyes, C.2
  • 9
    • 0000315335 scopus 로고    scopus 로고
    • Neuro-fuzzy clustering of radiographic tibia image data using type-2 fuzzy sets
    • R. I. John, P. R. Innocent, and M. R. Barnes, "Neuro-fuzzy clustering of radiographic tibia image data using type-2 fuzzy sets," Inf. Sci. vol. 125, pp. 203-220, 2000.
    • (2000) Inf. Sci , vol.125 , pp. 203-220
    • John, R.I.1    Innocent, P.R.2    Barnes, M.R.3
  • 12
    • 22044442216 scopus 로고    scopus 로고
    • A singular-value-QR decomposition based method for training fuzzy systems in uncertain environments
    • G. Mouzouris and J. M. Mendel, "A singular-value-QR decomposition based method for training fuzzy systems in uncertain environments," J. Intell. Fuzzy Syst., vol. 5, pp. 367-374, 1997.
    • (1997) J. Intell. Fuzzy Syst , vol.5 , pp. 367-374
    • Mouzouris, G.1    Mendel, J.M.2
  • 13
    • 0033078615 scopus 로고    scopus 로고
    • Simplifying fuzzy rule-based models using orthogonal transformation methods
    • Feb
    • J. Yen and L. Wang, "Simplifying fuzzy rule-based models using orthogonal transformation methods," IEEE Trans. Syst., Man, Cyber. B vol. 29, no. 1, pp. 13-24, Feb. 1999.
    • (1999) IEEE Trans. Syst., Man, Cyber. B , vol.29 , Issue.1 , pp. 13-24
    • Yen, J.1    Wang, L.2
  • 14
    • 0027601884 scopus 로고
    • ANFIS: Adaptive-network-based fuzzy inference system
    • May
    • J. S. Jang, "ANFIS: Adaptive-network-based fuzzy inference system," IEEE Trans. Syst., Man, Cybern., vol. 23, no. 3, pp. 665-685, May 1993.
    • (1993) IEEE Trans. Syst., Man, Cybern , vol.23 , Issue.3 , pp. 665-685
    • Jang, J.S.1
  • 15
    • 84974743850 scopus 로고
    • Fuzzy model identification based on cluster estimation
    • S. L. Chiu, "Fuzzy model identification based on cluster estimation," J. Intell. Fuzzy Syst., vol. 2, pp. 267-278, 1994.
    • (1994) J. Intell. Fuzzy Syst , vol.2 , pp. 267-278
    • Chiu, S.L.1
  • 16
    • 24644469161 scopus 로고    scopus 로고
    • A TSK-type neurofuzzy network approach to system modeling problems
    • Aug
    • C. S. Ouyang, W. J. Lee, and S. J. Lee, "A TSK-type neurofuzzy network approach to system modeling problems," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 35, no. 4, pp. 751-767, Aug. 2005.
    • (2005) IEEE Trans. Syst., Man, Cybern. B, Cybern , vol.35 , Issue.4 , pp. 751-767
    • Ouyang, C.S.1    Lee, W.J.2    Lee, S.J.3
  • 17
    • 0742290026 scopus 로고    scopus 로고
    • Identification of complex systems based on neural and Takagi-Sugeno fuzzy model
    • Feb
    • D. Kukolj and E. Levi, "Identification of complex systems based on neural and Takagi-Sugeno fuzzy model," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 34, no. 1, pp. 272-282, Feb. 2004.
    • (2004) IEEE Trans. Syst., Man, Cybern. B, Cybern , vol.34 , Issue.1 , pp. 272-282
    • Kukolj, D.1    Levi, E.2
  • 18
    • 0036530967 scopus 로고    scopus 로고
    • DENFIS: Dynamic evolving neural-fuzzy inference system and its application for time-series prediction
    • Apr
    • N. K. Kasabov and Q. Song, "DENFIS: Dynamic evolving neural-fuzzy inference system and its application for time-series prediction," IEEE Trans. Fuzzy Syst., vol. 10, no. 2, pp. 144-154, Apr. 2002.
    • (2002) IEEE Trans. Fuzzy Syst , vol.10 , Issue.2 , pp. 144-154
    • Kasabov, N.K.1    Song, Q.2
  • 19
    • 0742272554 scopus 로고    scopus 로고
    • An approach to online identification of Takagi-Sugeno fuzzy models
    • Feb
    • P. P. Angelov and D. Filev, "An approach to online identification of Takagi-Sugeno fuzzy models," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 34, no. 1, pp. 484-498, Feb. 2004.
    • (2004) IEEE Trans. Syst., Man, Cybern. B, Cybern , vol.34 , Issue.1 , pp. 484-498
    • Angelov, P.P.1    Filev, D.2
  • 21
    • 0033704546 scopus 로고    scopus 로고
    • Fuzzy modeling of high-dimensional systems: Complexity reduction and interpretability improvement
    • Apr
    • Y. Jin, "Fuzzy modeling of high-dimensional systems: Complexity reduction and interpretability improvement," IEEE Trans. Fuzzy Syst. vol. 8, no. 2, pp. 212-221, Apr. 2000.
    • (2000) IEEE Trans. Fuzzy Syst , vol.8 , Issue.2 , pp. 212-221
    • Jin, Y.1
  • 22
    • 9644257194 scopus 로고    scopus 로고
    • A multi-objective hierarchical genetic algorithm for interpretable rule-based knowledge extraction
    • H. Wang, S. Kwong, Y. Jin, W. Wei, and K. Man, "A multi-objective hierarchical genetic algorithm for interpretable rule-based knowledge extraction," Fuzzy Sets Syst., vol. 149, no. 1, pp. 149-186, 2005.
    • (2005) Fuzzy Sets Syst , vol.149 , Issue.1 , pp. 149-186
    • Wang, H.1    Kwong, S.2    Jin, Y.3    Wei, W.4    Man, K.5
  • 23
    • 4344685199 scopus 로고    scopus 로고
    • Interpretability and learning in neuro-fuzzy systems
    • R. Paiva and A. Dourado, "Interpretability and learning in neuro-fuzzy systems," Fuzzy Sets Syst., vol. 147, no. 1, pp. 17-38, 2004.
    • (2004) Fuzzy Sets Syst , vol.147 , Issue.1 , pp. 17-38
    • Paiva, R.1    Dourado, A.2
  • 24
    • 0034295771 scopus 로고    scopus 로고
    • Interval type-2 fuzzy logic systems: Theory and design
    • Oct
    • Q. Liang and J. M. Mendel, "Interval type-2 fuzzy logic systems: Theory and design," IEEE Trans. Fuzzy Syst., vol. 8, no. 5, pp. 535-550, Oct. 2000.
    • (2000) IEEE Trans. Fuzzy Syst , vol.8 , Issue.5 , pp. 535-550
    • Liang, Q.1    Mendel, J.M.2
  • 25
    • 2942640859 scopus 로고    scopus 로고
    • Systems identification using type-2 fuzzy neural network (Type-2 FNN) systems
    • C. H. Lee, Y. C. Lin, and W. Y. Lai, "Systems identification using type-2 fuzzy neural network (Type-2 FNN) systems," in Proc. IEEE Int. Symp. Comput. Intell. Robot. Autom., 2003, vol. 3, pp. 1264-1269.
    • (2003) Proc. IEEE Int. Symp. Comput. Intell. Robot. Autom , vol.3 , pp. 1264-1269
    • Lee, C.H.1    Lin, Y.C.2    Lai, W.Y.3
  • 26
    • 2942547512 scopus 로고    scopus 로고
    • Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN)
    • Jun
    • C. H. Wang, C. S. Cheng, and T. T. Lee, "Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN)," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 34, no. 3, pp. 1462-1477, Jun. 2004.
    • (2004) IEEE Trans. Syst., Man, Cybern. B, Cybern , vol.34 , Issue.3 , pp. 1462-1477
    • Wang, C.H.1    Cheng, C.S.2    Lee, T.T.3
  • 27
    • 1542273540 scopus 로고    scopus 로고
    • Computing derivatives in interval type-2 fuzzy logic system
    • Feb
    • J. M. Mendel, "Computing derivatives in interval type-2 fuzzy logic system," IEEE Trans. Fuzzy Syst., vol. 12, no. 1, pp. 84-98, Feb. 2004.
    • (2004) IEEE Trans. Fuzzy Syst , vol.12 , Issue.1 , pp. 84-98
    • Mendel, J.M.1
  • 28
    • 33749379258 scopus 로고    scopus 로고
    • Comments on dynamical optimal training for interval type-2 fuzzy neural network (T2FNN)
    • Oct
    • H. Hagras, "Comments on dynamical optimal training for interval type-2 fuzzy neural network (T2FNN)," IEEE Trans. Syst., Man Cybern. B, Cybern., vol. 36, no. 5, pp. 1206-1209, Oct. 2006.
    • (2006) IEEE Trans. Syst., Man Cybern. B, Cybern , vol.36 , Issue.5 , pp. 1206-1209
    • Hagras, H.1
  • 29
    • 23944507837 scopus 로고    scopus 로고
    • Interval type-2 TSK fuzzy logic systems using hybrid learning algorithm
    • May 22-25
    • G. M. Mendez and O. Castillo, "Interval type-2 TSK fuzzy logic systems using hybrid learning algorithm," in Proc. IEEE Int. Conf. Fuzzy Syst., May 22-25, 2005, pp. 230-235.
    • (2005) Proc. IEEE Int. Conf. Fuzzy Syst , pp. 230-235
    • Mendez, G.M.1    Castillo, O.2
  • 30
    • 0031999146 scopus 로고    scopus 로고
    • An on-line self-constructing neural fuzzy inference network and its applications
    • Feb
    • C. F. Juang and C. T. Lin, "An on-line self-constructing neural fuzzy inference network and its applications," IEEE Trans. Fuzzy Syst., vol. 6, no. 1, pp. 12-32, Feb. 1998.
    • (1998) IEEE Trans. Fuzzy Syst , vol.6 , Issue.1 , pp. 12-32
    • Juang, C.F.1    Lin, C.T.2
  • 32
    • 50249166470 scopus 로고    scopus 로고
    • A vector similarity measure for interval type-2 fuzzy sets
    • Jul
    • D. Wu and J. M. Mendel, "A vector similarity measure for interval type-2 fuzzy sets," in Proc. IEEE Int. Conf. Fuzzy Syst., Jul. 2007, pp. 1-6.
    • (2007) Proc. IEEE Int. Conf. Fuzzy Syst , pp. 1-6
    • Wu, D.1    Mendel, J.M.2
  • 33
    • 0025388355 scopus 로고
    • Estimating time-varying parameters by the Kalman filter based algorithm: Stability and convergence
    • Feb
    • L. Guo, "Estimating time-varying parameters by the Kalman filter based algorithm: Stability and convergence," IEEE Trans. Autom. Control vol. 35, no. 2, pp. 141-147, Feb. 1990.
    • (1990) IEEE Trans. Autom. Control , vol.35 , Issue.2 , pp. 141-147
    • Guo, L.1
  • 34
    • 34249668888 scopus 로고    scopus 로고
    • Nonlinear system identificationwith recurrent neural networks and dead-zone Kalman filter algorithm
    • J. J. Rubio and W. Yu, "Nonlinear system identificationwith recurrent neural networks and dead-zone Kalman filter algorithm," Neurocomputing, vol. 70, pp. 2460-2466, 2007.
    • (2007) Neurocomputing , vol.70 , pp. 2460-2466
    • Rubio, J.J.1    Yu, W.2
  • 36
    • 0036464756 scopus 로고    scopus 로고
    • The particle swarm - Explosion, stability, and convergence in a multidimentional complex space
    • Feb
    • M. Clerc and J. Kennedy, "The particle swarm - Explosion, stability, and convergence in a multidimentional complex space," IEEE Trans. Evol. Comput., vol. 6, no. 1, pp. 58-73, Feb. 2002.
    • (2002) IEEE Trans. Evol. Comput , vol.6 , Issue.1 , pp. 58-73
    • Clerc, M.1    Kennedy, J.2
  • 37
    • 0031268065 scopus 로고    scopus 로고
    • An ART-based fuzzy adaptive learning control network
    • Nov
    • C. J. Lin and C. T. Lin, "An ART-based fuzzy adaptive learning control network," IEEE Trans. Fuzzy Syst., vol. 5, no. 4, pp. 477-496, Nov. 1997.
    • (1997) IEEE Trans. Fuzzy Syst , vol.5 , Issue.4 , pp. 477-496
    • Lin, C.J.1    Lin, C.T.2
  • 38
    • 0031208449 scopus 로고    scopus 로고
    • An adaptive neural fuzzy filter and its applications
    • Aug
    • C. T. Lin and C. F. Juang, "An adaptive neural fuzzy filter and its applications," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 27, no. 4, pp. 635-656, Aug. 1997.
    • (1997) IEEE Trans. Syst., Man, Cybern. B, Cybern , vol.27 , Issue.4 , pp. 635-656
    • Lin, C.T.1    Juang, C.F.2
  • 39
    • 11144267886 scopus 로고    scopus 로고
    • Adaptive noise cancellation using type-2 fuzzy logic and neural networks
    • Jul
    • O. Castillo and P. Melin, "Adaptive noise cancellation using type-2 fuzzy logic and neural networks," in Proc. IEEE Int. Conf. Fuzzy Syst., Jul. 2004, vol. 2, pp. 1093-1098.
    • (2004) Proc. IEEE Int. Conf. Fuzzy Syst , vol.2 , pp. 1093-1098
    • Castillo, O.1    Melin, P.2
  • 40
    • 0030283350 scopus 로고    scopus 로고
    • Radial basis function based adaptive fuzzy systems and their applications to system identification
    • K. B. Cho and B. H. Wang, "Radial basis function based adaptive fuzzy systems and their applications to system identification," Fuzzy Sets Syst., vol. 83, pp. 325-339, 1996.
    • (1996) Fuzzy Sets Syst , vol.83 , pp. 325-339
    • Cho, K.B.1    Wang, B.H.2
  • 41
    • 0032845493 scopus 로고    scopus 로고
    • HyFIS: Adaptive neuro-fuzzy inference systems and their application to nonlinear dynamic systems
    • J. Kim and N. K. Kasabov, "HyFIS: Adaptive neuro-fuzzy inference systems and their application to nonlinear dynamic systems," Neural Netw., vol. 12, pp. 1301-1319, 1999.
    • (1999) Neural Netw , vol.12 , pp. 1301-1319
    • Kim, J.1    Kasabov, N.K.2
  • 42
    • 0001623515 scopus 로고    scopus 로고
    • Neuro-fuzzy systems for function approximation
    • D. Nauk and R. Kruse, "Neuro-fuzzy systems for function approximation," Fuzzy Sets Syst., vol. 101, no. 2, pp. 261-271, 1999.
    • (1999) Fuzzy Sets Syst , vol.101 , Issue.2 , pp. 261-271
    • Nauk, D.1    Kruse, R.2
  • 43
    • 0033692531 scopus 로고    scopus 로고
    • Dynamic fuzzy neural networks - A novel approach to function approximation
    • Apr
    • S. Wu and M. J. Er, "Dynamic fuzzy neural networks - A novel approach to function approximation," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 30, no. 2, pp. 358-364, Apr. 2000.
    • (2000) IEEE Trans. Syst., Man, Cybern. B, Cybern , vol.30 , Issue.2 , pp. 358-364
    • Wu, S.1    Er, M.J.2
  • 44
    • 0034266756 scopus 로고    scopus 로고
    • Genetic fuzzy learning
    • Sep
    • M. Russo, "Genetic fuzzy learning," IEEE Trans. Evol. Comput., vol. 4, no. 3, pp. 259-273, Sep. 2000.
    • (2000) IEEE Trans. Evol. Comput , vol.4 , Issue.3 , pp. 259-273
    • Russo, M.1
  • 45
    • 0036565201 scopus 로고    scopus 로고
    • Subsethood-product fuzzy neural inference system (SuPFuNIS)
    • May
    • S. Paul and S. Kumar, "Subsethood-product fuzzy neural inference system (SuPFuNIS)," IEEE Trans. Neural Netw., vol. 13, no. 3, pp. 578-599, May 2002.
    • (2002) IEEE Trans. Neural Netw , vol.13 , Issue.3 , pp. 578-599
    • Paul, S.1    Kumar, S.2
  • 46
    • 11244305511 scopus 로고    scopus 로고
    • NARMAX time series model prediction: Feedforward and recurrent fuzzy neural approaches
    • Y. Gao and M. J. Er, "NARMAX time series model prediction: Feedforward and recurrent fuzzy neural approaches," Fuzzy Sets Syst., vol. 150, pp. 331-350, 2005.
    • (2005) Fuzzy Sets Syst , vol.150 , pp. 331-350
    • Gao, Y.1    Er, M.J.2
  • 47
    • 34447257701 scopus 로고    scopus 로고
    • Automatic construction of feedforward/recurrent fuzzy systems by clustering-aided simplex particle swarm optimization
    • Sep
    • C. F. Juang, I. F. Chung, and C. H. Hsu, "Automatic construction of feedforward/recurrent fuzzy systems by clustering-aided simplex particle swarm optimization," Fuzzy Sets Syst., vol. 158, no. 18, pp. 1979-1996, Sep. 2007.
    • (2007) Fuzzy Sets Syst , vol.158 , Issue.18 , pp. 1979-1996
    • Juang, C.F.1    Chung, I.F.2    Hsu, C.H.3


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