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Volumn 47, Issue 3, 1995, Pages 247-268

Interference cancellation using radial basis function networks

Author keywords

Adaptive interference cancellation; Continuous and discrete signal models; Gaussian mixture basis function network; Normalized RBFN; Radial basis function networks; Stochastic gradient learning algorithm

Indexed keywords

ADAPTIVE FILTERING; APPROXIMATION THEORY; ELECTRIC NETWORK TOPOLOGY; FUNCTIONS; LEARNING ALGORITHMS; NEURAL NETWORKS; OPTIMIZATION; PERFORMANCE; SIGNAL PROCESSING; SIGNAL THEORY;

EID: 0029535654     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/0165-1684(95)00113-1     Document Type: Article
Times cited : (62)

References (20)
  • 5
    • 84916495433 scopus 로고
    • Radial basis function networks for nonlinear signal processing
    • University of Pennsylvania
    • (1995) Ph.D. Thesis
    • Cha1
  • 12
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik1
  • 15
    • 0000672424 scopus 로고
    • Fast learning in networks of locally-tuned processing units
    • (1989) Neural Networks , vol.1 , Issue.2 , pp. 281-294
    • Moody1    Darken2
  • 17
    • 0021404166 scopus 로고
    • Mixture densities, maximum likelihood and the EM algorithm
    • (1984) SIAM Rev. , vol.26 , pp. 195-239
    • Redner1    Walker2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.