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1.The Modified Steepest Descent Method──Best Point in Steepest Descent method
改进的最速下降法─最好点最速下降法收藏指正
2.Applications of Steepest Descent Arithmetic in Designing the MTD filters
最陡下降算法在MTD滤波器设计中的应用收藏指正
3.Based on the steepest descent method and the conjugate gradient method, a hybrid algorithm is proposed in this paper, and its global convergence is proved.
摘要将最速下降法与共扼梯度法有机结合起来，构造出一种混合优化算法，并证明其全局收敛性。收藏指正
4.steepest descent. The research of these problems has not been vended in the publication by now and the conclusions are not only brief and practicable but also the generation involving optimality conditions of Fritz John.
这些问题的研究至今为止还没有学者在刊物上公开发表过,所得到的结论不仅简洁、可行性强,而且是在可微情形下Fritz John最优性条件的推广.收藏指正
5.The hybrid algorithm raises the convergence rate of the conjugate gradient method and solves the problem for which the convergence rate of the steepest descent method get slower when the isopleth of goal function is oblong.
这种混合优化算法结合了共扼梯度法和最速下降法产生搜索方向，既提高了共扼梯度算法的收敛速度，又解决了目标函数的等值线是扁长椭球时，最速下降法下降缓慢的问题，具有收敛速度快、收敛范围大、适应面广等特点。收藏指正
6.In the image reconstruction based on optimization without constraint, the variable metric method, the steepest descent method, and conjugate gradient method were applied to image reconstruction to improve iterative efficiency and reconstructed quality, and their virtue and shortcoming were analyzed.
摘要在无约束最优化为基础的图像重建问题中，为了提高迭代效率以及重建图像质量，首次提出将变度量法应用到图像重建中。收藏指正
7.To deal with the defects of the steepest descent in slowly converging and easily immerging in partial minimum frequently, after analyzing the linear hunting method developed by Fletcher and Reeves, the improved conjugate gradient algorithm is brought forward to solve the problem.
针对一般BP算法收敛速度慢,易陷入局部极小值的缺陷,本文受Fletcher-Reeves线性搜索方法的指引,提出了基于改进共轭梯度法的BP算法。收藏指正
8.In this algorithm, Takagi Sugeno fuzzy neural network is used for the parametric learning of a fuzzy rule base with steepest descent method. Then, the structure of fuzzy rule bases is optimized with the binary coding method, in which a rule corresponds to a gene bit, and a rule base to a chromosome.
利用TakagiSugeno模糊神经网络对一个模糊规则基进行参数学习,学习方法为梯度下降法,然后利用遗传算法对规则基进行结构调整,采用二进制编码方法,一条规则对应于一个基因位,一个规则基对应于一条染色体。收藏指正
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