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AN OPTIMAL FUZZY APPROXIMATOR 被引量:1
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作者 YueShihong zhangkecun 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2002年第2期236-240,共5页
In a dot productspace with the reproducing kernel (r.k.S.) ,a fuzzy system with the estimation approximation errors is proposed,which overcomes the defect thatthe existing fuzzy control system is difficult to estima... In a dot productspace with the reproducing kernel (r.k.S.) ,a fuzzy system with the estimation approximation errors is proposed,which overcomes the defect thatthe existing fuzzy control system is difficult to estimate the errors of approximation for a desired function,and keeps the characteristics of fuzzy system as an inference approach.The structure of the new fuzzy approximator benefits a course got by other means 展开更多
关键词 reproducing kernel bounded linear functional fuzzy control
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A RECURSIVE QUADRATIC PROGRAMMING ALGORITHM THAT USES A NEW NONDIFFERENTIABLE PENALTY FUNCTIONS
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作者 YANGBOTING zhangkecun 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 1994年第1期95-103,共9页
In this papert a recursive quadratic programming algorithm is proposed andstudied.The line search functions used are Han's nondifferentiable penalty functionswith a second order penalty term. In order to avoid mar... In this papert a recursive quadratic programming algorithm is proposed andstudied.The line search functions used are Han's nondifferentiable penalty functionswith a second order penalty term. In order to avoid maratos effect,Fukushima's mixeddirection is used as the direction of line search.Finallyt we prove the global convergenceand the local second order convergence of the algorithm. 展开更多
关键词 Nonlinear Programming Line Search Penalty Function Maratos Efficient Convergence.
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A SUPERLINEARLY AND QUADRATICALLY CONVERGENT SQP TYPE FEASIBLE METHOD FOR CONSTRAINED OPTIMIZATION 被引量:3
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作者 JianJinbao zhangkecun XueShengjia 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2000年第3期319-331,共13页
A new SQP type feasible method for inequality constrained optimization is presented,it is a combination of a master algorithm and an auxiliary algorithm which is taken only in finite iterations.The directions of the m... A new SQP type feasible method for inequality constrained optimization is presented,it is a combination of a master algorithm and an auxiliary algorithm which is taken only in finite iterations.The directions of the master algorithm are generated by only one quadratic programming, and its step\|size is always one, the directions of the auxiliary algorithm are new “second\|order” feasible descent. Under suitable assumptions,the algorithm is proved to possess global and strong convergence, superlinear and quadratic convergence. 展开更多
关键词 Constrained optimization SQP feasible method convergence rate of convergence.
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