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Volumn 131, Issue 1-2, 2001, Pages 343-359

Solving nonlinear complementarity problems with neural networks: A reformulation method approach

Author keywords

Neural network; Nonlinear complementarity problem; Reformulation; Stability

Indexed keywords

ASYMPTOTIC STABILITY; CONVERGENCE OF NUMERICAL METHODS; LYAPUNOV METHODS; MATHEMATICAL MODELS; PROBLEM SOLVING;

EID: 0035361448     PISSN: 03770427     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0377-0427(00)00262-4     Document Type: Article
Times cited : (50)

References (35)
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    • Qi, L.1
  • 27
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    • Regular pseudo-smooth NCP and BVIP functions and globally and quadratically convergent generalized Newton methods for complementarity and variational inequality problems
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    • Qi, L.1
  • 28
    • 0031140591 scopus 로고    scopus 로고
    • Semismooth Karush-Kuhn-Tucker equations and convergence analysis of Newton and quasi-Newton methods for solving these equations
    • (1997) Math. Oper. Res , vol.22 , pp. 301-325
    • Qi, L.1    Jiang, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.