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Volumn 37, Issue 2, 2001, Pages 106-107

Adaptive training and pruning in feedforward networks

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CHARACTER RECOGNITION; COMPUTATIONAL COMPLEXITY; ITERATIVE METHODS; KALMAN FILTERING;

EID: 0035136577     PISSN: 00135194     EISSN: None     Source Type: Journal    
DOI: 10.1049/el:20010074     Document Type: Article
Times cited : (4)

References (4)
  • 1
    • 0026841022 scopus 로고
    • Real-time learning algorithm for a multilayered neural network based on the extended Kalman filter
    • IIGUNL, Y., SAKAI, H., and TOKUMARU, H.: 'Real-time learning algorithm for a multilayered neural network based on the extended Kalman filter', IEEE Trans. Signal Process., 1992, 40, pp. 959-967
    • (1992) IEEE Trans. Signal Process. , vol.40 , pp. 959-967
    • Iigunl, Y.1    Sakai, H.2    Tokumaru, H.3
  • 2
    • 0032777345 scopus 로고    scopus 로고
    • On the Kalman filtering method in neural-network training and pruning
    • SUM, J., LEUNG, C.S., YOUNG, G.H., and KAN, W.K.: 'On the Kalman filtering method in neural-network training and pruning', IEEE Trans. Neural Netw., 1999, 10, pp. 161-166
    • (1999) IEEE Trans. Neural Netw. , vol.10 , pp. 161-166
    • Sum, J.1    Leung, C.S.2    Young, G.H.3    Kan, W.K.4
  • 3
    • 0032484858 scopus 로고    scopus 로고
    • Energy function for learning invariant in multilayer perceptron
    • PENG, H., SHA, L., GAN, Q., and WEI, Y.: 'Energy function for learning invariant in multilayer perceptron', Electron. Lett., 1998, 34, pp. 292-294
    • (1998) Electron. Lett. , vol.34 , pp. 292-294
    • Peng, H.1    Sha, L.2    Gan, Q.3    Wei, Y.4
  • 4
    • 0030476783 scopus 로고    scopus 로고
    • Using spatio-temporal correlations to learn invariant object recognition
    • WALLIS, G.: 'Using spatio-temporal correlations to learn invariant object recognition', Neural Netw., 1996, 9, pp. 1513-1519
    • (1996) Neural Netw. , vol.9 , pp. 1513-1519
    • Wallis, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.