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Volumn 47, Issue 2, 2004, Pages 232-245

Finding roots of arbitrary high order polynomials based on neural network recursive partitioning method

Author keywords

Adaptive parameter selection; BP neural networks; Constrained learning algorithm; High order arbitrary polynomials; Jenkins Traub method; Laguerre method; Muller method; Real or complex roots; Recursive partitioning method

Indexed keywords


EID: 24944586784     PISSN: 10092757     EISSN: None     Source Type: Journal    
DOI: 10.1360/01yf0437     Document Type: Article
Times cited : (20)

References (16)
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    • Neural networks with problem decomposition for finding real roots of polynomials
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    • Finding complex roots of polynomials by feedforward neural networks
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    • Huang, D. S., Chi Zheru, Finding complex roots of polynomials by feedforward neural networks, 2001 Int. Joint Conf. on Neural Networks (IJCNN2001), Washington, DC, Vol. Addendum, July 15-19, 2001, 13-18.
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    • Dilation method for finding close roots of polynomials based on constrained learning neural networks
    • Huang, D. S., Ip, H. H. S., Chi Zheru et al., Dilation method for finding close roots of polynomials based on constrained learning neural networks, Physics Letters A, 2003, 309(5-6): 443-451.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.