the main work of the paper can be summarized as follows : 1 . a mixed hs-fr conjugate gradient algorithm is proposed . two convergence theorems without the sufficient descent condition for the mixed hs-fr algorithm are given 给出了一个混合的hs-fr共轭梯度算法,在无充分下降条件下,得到了关于hs-fr算法的两个收敛性定理。
this paper is devoted to some numerical optimization methods and optimization models for solving practical problems in real world . the methods we concern with are the conjugate gradient algorithms, evolutionary algorithms and goal programming 本文对近年来备受关注的几类最优化方法(共轭梯度算法、进化算法和目标规划法)的理论性质及应用进行了研究,主要研究成果如下:1
as for single objective optimization algorithm, a fast iterative algorithm based on conjugate gradient algorithm is presented, which makes use of extent limit of iterative optimization step in conjugate gradient with the idea of least square 在标量优化图像重建法中,作者以最小二乘为目标,利用共轭梯度法中迭代最优步长的区间性,提出了一种基于共轭梯度法的快速迭代算法。
in this thesis, some kinds of learning algorithms of feed-forward neural network have been analyzed; later a scaled conjugate gradient algorithm is presented to train network, furthermore, modified training methods have been provided to improve the neural network performance 在分析比较了几种前馈神经网络的学习算法后,提出尺度共轭梯度算法对网络进行训练,并针对现有网络训练方法提出了改进。
under the frame of natural gradient algorithm, an ica algorithm based on adaptive kernel estimation is proposed, which can separate arbitrary mixed signals ( such as super-gaussian and sub-gaussian, symmetric and asymmetric signals ) 摘要在自然梯度算法的框架下,本文利用随机变量概率密度函数非参数估计的自适应核函数法,给出了一种能够对任意混合信号(超高斯和亚高斯信号,对称和非对称分布信号)进行盲分离的算法。