a class of algorithms for unconstrained nondifferentiable programming 一類無約束不可微規(guī)劃算法
firstly, this thesis introduces the present situation of the research and methods of medical image registration . the major classes of algorithms and relative techniques are reviewed and several specific examples of each class of algorithm are described 本文首先介紹了醫(yī)學圖像配準研究的現(xiàn)狀和方法,對各類配準算法及其相關技術進行了綜述,并大量分析了各類方法的不同應用實例。
firstly, this thesis introduces the present situation of the research and methods of medical image registration . the major classes of algorithms and relative techniques are reviewed and several specific examples of each class of algorithm are described 本文首先介紹了醫(yī)學圖像配準研究的現(xiàn)狀和方法,對各類配準算法及其相關技術進行了綜述,并大量分析了各類方法的不同應用實例。
in this paper, a class of algorithms which are update quasi-newton methods for unconstrained optimization as follows : this article consists, of three parts . the first part is the introduction of the quasi-newton methods for unconstrained optimization . the second part is the proof of the global and superlin-early convergence of the generalized-quasi-newton methods . the third part is quasi-newton-non-convex class methods and its global convergence . the main results of the second part are as follows : theorem of global convergence 在第一章中,主要是根據(jù)焦寶聰提出的廣義擬牛頓算法,對目標函數(shù)放寬了條件限制,結合goldstein線性搜索,對一般目標函數(shù)進行了收斂性的討論,其主要結果如下:全局收斂性定理若f(x)在r~n上二次連續(xù)可微,有下界,水平集。