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Volumn 52, Issue 1, 2005, Pages 207-221

An on-line ICA-mixture-model-based self-constructing fuzzy neural network

Author keywords

Backpropagation rule; Gaussian mixture model; Non Gaussian mixture model; Principal component analysis; Takagi Sugeno Kang (TSK) fuzzy rules

Indexed keywords

BACKPROPAGATION; FUZZY SETS; IDENTIFICATION (CONTROL SYSTEMS); INDEPENDENT COMPONENT ANALYSIS; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; PRINCIPAL COMPONENT ANALYSIS;

EID: 12944295084     PISSN: 10577122     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCSI.2004.840110     Document Type: Article
Times cited : (51)

References (42)
  • 6
    • 0026923902 scopus 로고
    • "On fuzzy modeling using fuzzy neural networks with the backpropagation algorithm"
    • Sep
    • S. Horikawa, T. Furuhashi, and Y. Uchikawa, "On fuzzy modeling using fuzzy neural networks with the backpropagation algorithm," IEEE Trans. Neural Netw., vol. 3, pp. 801-806, Sep. 1992.
    • (1992) IEEE Trans. Neural Netw. , vol.3 , pp. 801-806
    • Horikawa, S.1    Furuhashi, T.2    Uchikawa, Y.3
  • 7
    • 0029358133 scopus 로고
    • "Modeling and control of carbon monoxide concentration using a neuro-fuzzy technique"
    • Aug
    • K. Tanaka, M. Sano, and H. Watanabe, "Modeling and control of carbon monoxide concentration using a neuro-fuzzy technique," IEEE Trans. Fuzzy Syst., vol. 3, pp. 271-279, Aug. 1995.
    • (1995) IEEE Trans. Fuzzy Syst. , vol.3 , pp. 271-279
    • Tanaka, K.1    Sano, M.2    Watanabe, H.3
  • 8
    • 84941531642 scopus 로고
    • "A new approach to fuzzy-neural system modeling"
    • May
    • Y. Lin and G. A. Cunningham, "A new approach to fuzzy-neural system modeling," IEEE Trans. Fuzzy Syst., vol. 3, pp. 190-197, May 1995.
    • (1995) IEEE Trans. Fuzzy Syst. , vol.3 , pp. 190-197
    • Lin, Y.1    Cunningham, G.A.2
  • 9
    • 0027544110 scopus 로고
    • "A fuzzy-logic-based approach to qualitative modeling"
    • Feb
    • M. Sugeno and T. Yasukawa, "A fuzzy-logic-based approach to qualitative modeling," IEEE Trans. Fuzzy Syst., vol. 1, pp. 7-31, Feb. 1993.
    • (1993) IEEE Trans. Fuzzy Syst. , vol.1 , pp. 7-31
    • Sugeno, M.1    Yasukawa, T.2
  • 10
    • 0029406441 scopus 로고
    • "Building sugeno-type models using fuzzy discretization and orthogonal parameter estimation techniques"
    • Nov
    • L. Wang and R. Langari, "Building sugeno-type models using fuzzy discretization and orthogonal parameter estimation techniques," IEEE Trans. Fuzzy Syst., vol. 3, pp. 454-458, Nov. 1995.
    • (1995) IEEE Trans. Fuzzy Syst. , vol.3 , pp. 454-458
    • Wang, L.1    Langari, R.2
  • 11
  • 12
    • 84899004910 scopus 로고    scopus 로고
    • "Unsupervised classification with nongaussian mixture models using ICA"
    • T. W. Lee, M. S. Lewicki, and T. J. Sejnowski, "Unsupervised classification with nongaussian mixture models using ICA," Adv. Neural Inf. Process. Syst., vol. 11, pp. 508-514, 1999.
    • (1999) Adv. Neural Inf. Process. Syst. , vol.11 , pp. 508-514
    • Lee, T.W.1    Lewicki, M.S.2    Sejnowski, T.J.3
  • 13
    • 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
  • 14
    • 0033556834 scopus 로고    scopus 로고
    • "Independent component analysis using an extended infomax algorithm for mixed sub-gaussian and super-gaussian sources"
    • T. W. Lee, M. Girolami, and T. J. Sejnowski, "Independent component analysis using an extended infomax algorithm for mixed sub-gaussian and super-gaussian sources," Neural Comput., vol. 11, no. 2, pp. 417-441, 1999.
    • (1999) Neural Comput. , vol.11 , Issue.2 , pp. 417-441
    • Lee, T.W.1    Girolami, M.2    Sejnowski, T.J.3
  • 19
    • 10844236785 scopus 로고    scopus 로고
    • "Image processing methods using ICA mixture models"
    • S. Roberts and R. Everson, Eds. New York: Cambridge Univ. Press
    • T.-W. Lee and M. S. Lewicki, "Image processing methods using ICA mixture models," in Independent Component Analysis: Principles and Practice, S. Roberts and R. Everson, Eds. New York: Cambridge Univ. Press, 2001.
    • (2001) Independent Component Analysis: Principles and Practice
    • Lee, T.-W.1    Lewicki, M.S.2
  • 21
    • 0033556788 scopus 로고    scopus 로고
    • "Mixtures of probabilistic principal component analyzers"
    • M. E. Tipping and C. M. Bishop, "Mixtures of probabilistic principal component analyzers," Neural Computation, vol. 11, no. 2, pp. 443-482, 1999.
    • (1999) Neural Computation , vol.11 , Issue.2 , pp. 443-482
    • Tipping, M.E.1    Bishop, C.M.2
  • 22
    • 0034133184 scopus 로고    scopus 로고
    • "Learning overcomplete representations"
    • M. S. Lewicki and T. J. Sejnowski, "Learning overcomplete representations," Neural Computation, vol. 12, no. 2, pp. 337-365, 2000.
    • (2000) Neural Computation , vol.12 , Issue.2 , pp. 337-365
    • Lewicki, M.S.1    Sejnowski, T.J.2
  • 23
    • 0003905755 scopus 로고    scopus 로고
    • Maximum Likelihood and Covariant Algorithms for Independent Component Analysis
    • Draft 3.7
    • D. MacKay, Maximum Likelihood and Covariant Algorithms for Independent Component Analysis, Draft 3.7, 1996.
    • (1996)
    • Mackay, D.1
  • 24
    • 0033878613 scopus 로고    scopus 로고
    • "Blind signal separation in teleconferencing using the ICA mixture model"
    • U.-M. Bae and T.-W. Lee, "Blind signal separation in teleconferencing using the ICA mixture model," Electron. Lett., vol. 36, no. 7, pp. 680-382, 2000.
    • (2000) Electron. Lett. , vol.36 , Issue.7 , pp. 382-680
    • Bae, U.-M.1    Lee, T.-W.2
  • 25
    • 0032612381 scopus 로고    scopus 로고
    • "High-order contrasts for independent component analysis"
    • J. F. Cardoso, "High-order contrasts for independent component analysis," Neural Comput., vol. 11, pp. 157-192, 1999.
    • (1999) Neural Comput. , vol.11 , pp. 157-192
    • Cardoso, J.F.1
  • 27
    • 0034290916 scopus 로고    scopus 로고
    • "ICA mixture models for unsupervised classification of non-Gaussian classes and automatic context switching in blind signal separation"
    • Oct
    • T. W. Lee, M. S. Lewicki, and T. J. Sejnowski, "ICA mixture models for unsupervised classification of non-Gaussian classes and automatic context switching in blind signal separation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 10, Oct. 2000.
    • (2000) IEEE Trans. Pattern Anal. Mach. Intell. , vol.22 , Issue.10
    • Lee, T.W.1    Lewicki, M.S.2    Sejnowski, T.J.3
  • 28
    • 0011006550 scopus 로고    scopus 로고
    • "ICA mixture models for unsupervised and automatic context switching"
    • T. W. Lee, M. S. Lewicki, and T. J. Sejnowski, "ICA mixture models for unsupervised and automatic context switching," in Proc. Int. Workshop ICA, 1999, pp. 209-214.
    • (1999) Proc. Int. Workshop ICA , pp. 209-214
    • Lee, T.W.1    Lewicki, M.S.2    Sejnowski, T.J.3
  • 29
    • 0042525838 scopus 로고    scopus 로고
    • "A constructive algorithm for training cooperative neural network ensembles"
    • Jul
    • Md. M. Islam, X. Yao, and K. Murase, "A constructive algorithm for training cooperative neural network ensembles," IEEE Trans. Neural Netw., vol. 14, no. 4, Jul. 2003.
    • (2003) IEEE Trans. Neural Netw. , vol.14 , Issue.4
    • Islam, Md.M.1    Yao, X.2    Murase, K.3
  • 31
    • 0026927202 scopus 로고
    • "Fuzzy min-max neural networks - Part I: Classification"
    • Sep
    • P. K. Simpson, "Fuzzy min-max neural networks - Part I: Classification," IEEE Trans. Neural Netw., vol. 3, pp. 776-786, Sep. 1992.
    • (1992) IEEE Trans. Neural Netw. , vol.3 , pp. 776-786
    • Simpson, P.K.1
  • 32
    • 0032144971 scopus 로고    scopus 로고
    • "A neural network classifier with disjunctive fuzzy information"
    • H. M. Lee, "A neural network classifier with disjunctive fuzzy information," Neural Netw., vol. 11, no. 6, pp. 1113-1125, 1998.
    • (1998) Neural Netw. , vol.11 , Issue.6 , pp. 1113-1125
    • Lee, H.M.1
  • 33
    • 0035359279 scopus 로고    scopus 로고
    • "An efficient fuzzy classifier with feature selection based on fuzzy entropy"
    • Jun
    • H. M. Lee, C. M. Chen, J. M. Chen, and Y. L. Jou, "An efficient fuzzy classifier with feature selection based on fuzzy entropy," IEEE Trans. Syst., Man, Cybern. B, vol. 31, pp. 426-432, Jun. 2001.
    • (2001) IEEE Trans. Syst., Man, Cybern. B , vol.31 , pp. 426-432
    • Lee, H.M.1    Chen, C.M.2    Chen, J.M.3    Jou, Y.L.4
  • 34
    • 0033078158 scopus 로고    scopus 로고
    • "A new method for constructing membership functions and fuzzy roles from training examples"
    • Feb
    • T. P. Wu and S. M. Chen, "A new method for constructing membership functions and fuzzy roles from training examples," IEEE Trans. on Syst. Man, Cybern. B, Cybern., vol. 29, pp. 25-40, Feb. 1999.
    • (1999) IEEE Trans. on Syst. Man, Cybern. B, Cybern. , vol.29 , pp. 25-40
    • Wu, T.P.1    Chen, S.M.2
  • 35
    • 0036902547 scopus 로고    scopus 로고
    • "Self-adaptive neuro-fuzzy inference systems for classification applications"
    • Dec
    • J. S. Wang and C. S. George Lee, "Self-adaptive neuro-fuzzy inference systems for classification applications," IEEE Trans. Fuzzy Syst. vol. 10, no. 6, Dec. 2002.
    • (2002) IEEE Trans. Fuzzy Syst. , vol.10 , Issue.6
    • Wang, J.S.1    George Lee, C.S.2
  • 37
    • 0001703957 scopus 로고    scopus 로고
    • "A neuro-fuzzy method to learn fuzzy classification rules from data"
    • D. Nauck and R. Kruse, "A neuro-fuzzy method to learn fuzzy classification rules from data," Fuzzy Sets Syst., vol. 89, no. 3, pp. 277-288, 1997.
    • (1997) Fuzzy Sets Syst. , vol.89 , Issue.3 , pp. 277-288
    • Nauck, D.1    Kruse, R.2
  • 38
    • 0031140388 scopus 로고    scopus 로고
    • "Neural-network feature selector"
    • Jun
    • R. Setiono and H. Liu, "Neural-network feature selector," IEEE Trans. Neural Netw., vol. 8, no. 3, pp. 654-662, Jun. 1997.
    • (1997) IEEE Trans. Neural Netw. , vol.8 , Issue.3 , pp. 654-662
    • Setiono, R.1    Liu, H.2
  • 39
    • 0034294243 scopus 로고    scopus 로고
    • "GA-fuzzy modeling and classification: Complexity and performance"
    • Oct
    • M. Setnes and H. Roubos, "GA-fuzzy modeling and classification: Complexity and performance," IEEE Trans. Fuzzy Syst., vol. 8, no. 5, pp. 509-522, Oct. 2000.
    • (2000) IEEE Trans. Fuzzy Syst. , vol.8 , Issue.5 , pp. 509-522
    • Setnes, M.1    Roubos, H.2
  • 40
    • 0032597810 scopus 로고    scopus 로고
    • "Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problems"
    • Oct
    • H. Ishibuchi, T. Nakashima, and T. Murata, "Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problems," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 29, pp. 601-618, Oct. 1999.
    • (1999) IEEE Trans. Syst., Man, Cybern. B, Cybern. , vol.29 , pp. 601-618
    • Ishibuchi, H.1    Nakashima, T.2    Murata, T.3
  • 41
    • 0028582717 scopus 로고
    • "Using real-valued genetic algorithms to evolve role sets for classification"
    • Orlando, FL, Jun
    • A. L. Corcoran and S. Sen, "Using real-valued genetic algorithms to evolve role sets for classification," in Proc. 1st IEEE Conf. Evolutionary Computation, Orlando, FL, Jun. 1994, pp. 120-124.
    • (1994) Proc. 1st IEEE Conf. Evolutionary Computation , pp. 120-124
    • Corcoran, A.L.1    Sen, S.2
  • 42
    • 33646223725 scopus 로고    scopus 로고
    • LIACC, Univ. of Porto Rua Campo Alegre 823 4150 Porto, Portugal
    • P. Brazdil and J. Gama, LIACC, Univ. of Porto Rua Campo Alegre 823 4150 Porto, Portugal.
    • Brazdil, P.1    Gama, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.