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Volumn 3496, Issue I, 2005, Pages 455-460

A novel generalized congruence neural networks

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; LEARNING ALGORITHMS; PROBLEM SOLVING;

EID: 24944506938     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11427391_72     Document Type: Conference Paper
Times cited : (4)

References (13)
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    • Chandra, P., Singh, Y.: A Case for the Self-adaptation of Activation Functions in FFANNs. Neurocomputing, 56 (2004) 447-454
    • (2004) Neurocomputing , vol.56 , pp. 447-454
    • Chandra, P.1    Singh, Y.2
  • 3
    • 0028461628 scopus 로고
    • A unified framework for MLPs and RBFNs: Introducing conic section function networks
    • Dorffner, G.: A Unified Framework for MLPs and RBFNs: Introducing Conic Section Function Networks. Cybernetics and Systems, 25 (1994) 511-554
    • (1994) Cybernetics and Systems , vol.25 , pp. 511-554
    • Dorffner, G.1
  • 5
    • 33847146183 scopus 로고    scopus 로고
    • Architectures and algorithms of generalized gongruence neural networks
    • Jin, F.: Architectures and Algorithms of Generalized Gongruence Neural Networks. Journal of Southwest Jiaotong University, 6 (1998)
    • (1998) Journal of Southwest Jiaotong University , vol.6
    • Jin, F.1
  • 6
    • 24944504494 scopus 로고    scopus 로고
    • Study on principles and algorithms of generalized congruence neural networks
    • Publishing House of Electronics Industry, Beijing
    • Jin, F.: Study on Principles and Algorithms of Generalized Congruence Neural Networks. International Conference on Neural Network and Brain. Publishing House of Electronics Industry, Beijing (1998) 441-444
    • (1998) International Conference on Neural Network and Brain , pp. 441-444
    • Jin, F.1
  • 7
    • 0035299214 scopus 로고    scopus 로고
    • Analysis of characteristics of generalized congruence neural networks with an improved algorithm
    • Hu, F., Jin, F.: Analysis of Characteristics of Generalized Congruence Neural Networks with an Improved Algorithm. Journal of Southwest Jiaotong University, 36 (2001) 136-139
    • (2001) Journal of Southwest Jiaotong University , vol.36 , pp. 136-139
    • Hu, F.1    Jin, F.2
  • 8
    • 0033077409 scopus 로고    scopus 로고
    • Fast convergent generalized back-propagation algorithm with constant learning rate
    • NG, S.C., LEUNG, S.H., LUK, A.: Fast Convergent Generalized Back-propagation Algorithm with Constant Learning Rate. Neural Processing Letters, 9 (1999) 13-23
    • (1999) Neural Processing Letters , vol.9 , pp. 13-23
    • Ng, S.C.1    Leung, S.H.2    Luk, A.3
  • 9
    • 0000389960 scopus 로고
    • Constructing hidden units using examples and queries
    • Lippmann, R., Moody, J., Touretzky, D.(eds.): Morgan Kaufmann, San Mateo, CA
    • Baum, E., Lang, K.: Constructing Hidden Units Using Examples and Queries. In Lippmann, R., Moody, J., Touretzky, D.(eds.): Advances in Neural Information Processing Systems. Vol. 3. Morgan Kaufmann, San Mateo, CA (1991) 904-910
    • (1991) Advances in Neural Information Processing Systems , vol.3 , pp. 904-910
    • Baum, E.1    Lang, K.2
  • 10
    • 0030104504 scopus 로고    scopus 로고
    • Global optimization for neural network training
    • Shang, Y., Wah, B.W.: Global optimization for Neural Network Training. IEEE Computer, 29 (1996) 45-54
    • (1996) IEEE Computer , vol.29 , pp. 45-54
    • Shang, Y.1    Wah, B.W.2
  • 11
    • 0032935466 scopus 로고    scopus 로고
    • Training multilayer neural networks using fast global learning algorithm-least-squares and penalized optimization methods
    • Cho, S., Chow, T.W.S.: Training Multilayer Neural Networks Using Fast Global Learning Algorithm-least-squares and Penalized Optimization Methods. Neurocomputing, 25 (1999) 115-131
    • (1999) Neurocomputing , vol.25 , pp. 115-131
    • Cho, S.1    Chow, T.W.S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.