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Volumn 5, Issue 4, 2006, Pages 639-658

Constrained formulations and algorithms for predicting stock prices by recurrent FIR neural networks

Author keywords

Channel specific low pass filtering; Edge effects; Non stationarity; Nonlinear constrained optimization; Recurrent FIR neural networks; Stock prices; Time series predictions; Wavelet decomposition

Indexed keywords


EID: 33845506447     PISSN: 02196220     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219622006002209     Document Type: Article
Times cited : (8)

References (21)
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    • Hellstrom, T.1    Holmstrom, K.2
  • 12
    • 0004181307 scopus 로고
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    • Violation-guided learning for constrained formulations in neural network time series prediction
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.