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基于高通滤波器的半全局极值搜索算法研究 被引量:3
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作者 张雷 胡云安 卢斌文 《科学技术与工程》 北大核心 2012年第29期7580-7584,共5页
针对半全局极值搜索算法的准确性和快速性之间存在相互制约的问题,提出了采用高通滤波器过滤反馈信号中的低频信号。用平均化方法证明了系统保持了半全局收敛性,放宽了对反馈增益要求较小参数的限制,还兼顾了系统的准确性和快速性。通... 针对半全局极值搜索算法的准确性和快速性之间存在相互制约的问题,提出了采用高通滤波器过滤反馈信号中的低频信号。用平均化方法证明了系统保持了半全局收敛性,放宽了对反馈增益要求较小参数的限制,还兼顾了系统的准确性和快速性。通过仿真对比发现基于高通滤波器的半全局极值搜索算法保持了系统半全局收敛性,提高了系统准确性和快速性。 展开更多
关键词 全局极值搜索算法 高通滤波器 半全局收敛性 准确 快速
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基于方波信号的半全局极值搜索算法
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作者 张雷 胡云安 左斌 《海军航空工程学院学报》 2012年第4期366-370,共5页
针对半全局极值搜索算法,采用正弦信号作为激励信号时,幅值自适应律初始值选取严格、输出存在颤振的问题,提出了采用方波信号作为激励信号。利用平均化方法证明了激励信号选取较小的初始值即可使目标函数收敛到全局极值,同时减弱了输出... 针对半全局极值搜索算法,采用正弦信号作为激励信号时,幅值自适应律初始值选取严格、输出存在颤振的问题,提出了采用方波信号作为激励信号。利用平均化方法证明了激励信号选取较小的初始值即可使目标函数收敛到全局极值,同时减弱了输出颤振;采用正弦和方波信号作为激励信号进行仿真对比,说明方波信号可以提高算法的半全局收敛性,有效减弱输出颤振。 展开更多
关键词 极值搜索算法 方波信号 半全局收敛性 输出颤振
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An entropy based central cutting plane algorithm for convex min-max semi-infinite programming problems 被引量:2
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作者 ZHANG LiPing FANG Shu-Cherng WU Soon-Yi 《Science China Mathematics》 SCIE 2013年第1期201-211,共11页
In this paper,we present a central cutting plane algorithm for solving convex min-max semi-infinite programming problems.Because the objective function here is non-differentiable,we apply a smoothing technique to the ... In this paper,we present a central cutting plane algorithm for solving convex min-max semi-infinite programming problems.Because the objective function here is non-differentiable,we apply a smoothing technique to the considered problem and develop an algorithm based on the entropy function.It is shown that the global convergence of the proposed algorithm can be obtained under weaker conditions.Some numerical results are presented to show the potential of the proposed algorithm. 展开更多
关键词 semi-infinite programming min-max problem central cutting plane ENTROPY
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GLOBAL CONVERGENCE OF A CLASS OF SMOOTH PENALTY METHODS FOR SEMI-INFINITE PROGRAMMING
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作者 Changyu WANG Haiyan ZHANG Fang LIU 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2011年第4期769-783,共15页
For the semi-infinite programming (SIP) problem, the authors first convert it into an equivalent nonlinear programming problem with only one inequality constraint by using an integral function, and then propose a sm... For the semi-infinite programming (SIP) problem, the authors first convert it into an equivalent nonlinear programming problem with only one inequality constraint by using an integral function, and then propose a smooth penalty method based on a class of smooth functions. The main feature of this method is that the global solution of the penalty function is not necessarily solved at each iteration, and under mild assumptions, the method is always feasible and efficient when the evaluation of the integral function is not very expensive. The global convergence property is obtained in the absence of any constraint qualifications, that is, any accumulation point of the sequence generated by the algorithm is the solution of the SIP. Moreover, the authors show a perturbation theorem of the method and obtain several interesting results. Furthermore, the authors show that all iterative points remain feasible after a finite number of iterations under the Mangasarian-Fromovitz constraint qualification. Finally, numerical results are given. 展开更多
关键词 Global convergence semi-infinite programming smooth penalty function perturbation function.
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