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Volumn 3610, Issue PART I, 2005, Pages 293-302

An algorithm for pruning redundant modules in min-max modular network with GZC function

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; FUNCTIONS; NEURAL NETWORKS; REDUNDANCY;

EID: 26844520013     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11539087_35     Document Type: Conference Paper
Times cited : (2)

References (18)
  • 1
    • 84902215278 scopus 로고    scopus 로고
    • Task decomposition based on class relations: A modular neural network architecture for pattern classification
    • Springer
    • Lu, B.L. and Ito, M.: Task decomposition based on class relations: a modular neural network architecture for pattern classification. Lecture Notes in Computer Science, Springer vol. 1240(1997)330-339
    • (1997) Lecture Notes in Computer Science , vol.1240 , pp. 330-339
    • Lu, B.L.1    Ito, M.2
  • 2
    • 0032594843 scopus 로고    scopus 로고
    • Task decomposition and module combination based on class relations: A modular neural network for pattern classification
    • Lu, B.L. and Ito, M.: Task Decomposition and Module Combination Based on Class Relations: A Modular Neural Network for Pattern Classification. IEEE Trans. Neural Networks, vol.10 (1999) 1244-1256
    • (1999) IEEE Trans. Neural Networks , vol.10 , pp. 1244-1256
    • Lu, B.L.1    Ito, M.2
  • 3
    • 0038265199 scopus 로고    scopus 로고
    • Efficient part-of-speech tagging with a min-max modular neural network model
    • Lu, B.L., Ma, Q., Ichikawa,M. and Isahara, H.: Efficient Part-of-Speech Tagging with a Min-Max Modular Neural Network Model. Applied Intelligence, vol. 19 (2003)65-81
    • (2003) Applied Intelligence , vol.19 , pp. 65-81
    • Lu, B.L.1    Ma, Q.2    Ichikawa, M.3    Isahara, H.4
  • 4
    • 1242300104 scopus 로고    scopus 로고
    • Massively parallel classification of single-trial EEG signals using a min-max modular neural network
    • Lu, B.L., Shin, J., and Ichikawa, M.: Massively Parallel Classification of Single-Trial EEG Signals Using a Min-Max Modular Neural Network. IEEE Trans. Biomedical Engineering, vol.51, (2004) 551-558
    • (2004) IEEE Trans. Biomedical Engineering , vol.51 , pp. 551-558
    • Lu, B.L.1    Shin, J.2    Ichikawa, M.3
  • 7
    • 0036085323 scopus 로고    scopus 로고
    • Emergent on-line learning with a gaussian zero-crossing discriminant function
    • Lu, B.L. and Ichikawa, M.: Emergent On-Line Learning with a Gaussian Zero-Crossing Discriminant Function. IJCNN '02, vol.2 (2002) 1263-1268
    • (2002) IJCNN '02 , vol.2 , pp. 1263-1268
    • Lu, B.L.1    Ichikawa, M.2
  • 8
    • 84931162639 scopus 로고
    • The condensed nearest neighbor rule
    • Hart, P.E.: The Condensed Nearest Neighbor Rule. IEEE Trans. Information Theory, vol.14 (1968) 515-516
    • (1968) IEEE Trans. Information Theory , vol.14 , pp. 515-516
    • Hart, P.E.1
  • 9
    • 0015346497 scopus 로고
    • The reduced nearest neighbor rule
    • Gates, G.W.: The Reduced Nearest Neighbor Rule. IEEE Trans. Information Theory, vol.18 (1972) 431-433
    • (1972) IEEE Trans. Information Theory , vol.18 , pp. 431-433
    • Gates, G.W.1
  • 10
    • 0015361129 scopus 로고
    • Asympotic propoties of nearest neighbor rules using edited data
    • Wilson, D.L.: Asympotic propoties of nearest neighbor rules using edited data. IEEE trans. System, Man, and Cybernetics, vol.2, No.3 (1972) 431-433
    • (1972) IEEE Trans. System, Man, and Cybernetics , vol.2 , Issue.3 , pp. 431-433
    • Wilson, D.L.1
  • 11
    • 0025725905 scopus 로고
    • Instance-based learning algorithm
    • Aha, D.W., Dennis, K. and Mack, K.A.: Instance-based learning algorithm. Machine Learning, vol.6 (1991) 37-66
    • (1991) Machine Learning , vol.6 , pp. 37-66
    • Aha, D.W.1    Dennis, K.2    Mack, K.A.3
  • 13
    • 0036684204 scopus 로고    scopus 로고
    • Discovering useful concept prototypes for classification based on filtering and abstraction
    • Wai, L., Keung, C.K. and Liu, D.Y.: Discovering useful concept prototypes for classification based on filtering and abstraction. IEEE Trans. Pattern Analysis and Machine Intelligence, vol.24, No.8 (2002) 1075-1090
    • (2002) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.24 , Issue.8 , pp. 1075-1090
    • Wai, L.1    Keung, C.K.2    Liu, D.Y.3
  • 16
    • 24944588472 scopus 로고    scopus 로고
    • Typical sample selection and redundancy reduction for min-max modular network with GZC function
    • Lecture Notes in Computer Science
    • Li, J., Lu, B.L. and Ichikawa, M.: Typical Sample Selection and Redundancy Reduction for Min-Max Modular Network with GZC Function. ISNN'05, Lecture Notes in Computer Science, (2005) 467-472
    • (2005) ISNN'05 , pp. 467-472
    • Li, J.1    Lu, B.L.2    Ichikawa, M.3
  • 17
    • 10944220472 scopus 로고    scopus 로고
    • A part-versus-part method for massively parallel training of support vector machines
    • Budapast, July25-29
    • Lu, B.L., Wang, K.A., Utiyama, M. and Isahara, H.: A part-versus-part method for massively parallel training of support vector machines. Proceedings of IJCNN'04, Budapast, July25-29 (2004) 735-740.
    • (2004) Proceedings of IJCNN'04 , pp. 735-740
    • Lu, B.L.1    Wang, K.A.2    Utiyama, M.3    Isahara, H.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.