matlab prepared by BP neural network algorithm, a small process applications

本程序利用遗传算法解决一简单的多项式极值问题-This procedure using the genetic algorithm to solve a simple problem of polynomial extremal

神 经 网 络 资 料-neural network data

PCA codes for face detection

这是好用的源代码-This is the source code handy

粒子群算法的vb源程序，可以自定义算法参数，实现对6个非约束性测试函数极小值的全局优化，动态显示粒子的移动。低维下，优化效果很好。直接解压，无须密码。请多指正。-PSO algorithm vb source, the algorithm can define parameters to achieve the six non-binding function tests minimum of global optimization, dynamic display particle movement. Low-dimensional, optimize the results very good. Direct decompression without passwords. Please correct.

lvq神经网络 的编程 希望大家能用的上-lvq neural network programming hope everyone can be on the

基于机器学习的自动逻辑推理机。本程序用归结反演策略实现了命题逻辑系统的自动推理。把要解决的问题作为一个要证明的命题，其目标公式被否定并化成子句形，然后添加到命题公式集中去,把消解反演系统应用于联合集，并推导出一个空子句(NIL)，产生一个矛盾。-based on the automatic machine learning logical reasoning machine. The procedures used attributed inversion strategy to achieve the propositional logic of automatic reasoning. Put the problem to be solved as a proposition to prove, with the goal being negated formula and shape into a phrase and then added to the Proposition formula to concentrate, digestion system for joint inversion sets and derived an empty phrase (NIL), resulting in a contradiction.

Matlab遗传算法工具箱函数及应用实例 Matlab遗传算法工具箱函数及应用实例-Matlab genetic algorithm toolbox function and application of genetic algorithm Matlab toolbox function and application example

这是一个笔者撰写改进了别人的隐马尔可夫模型算法的程序。-This is a writer writing improvement of the people"s hidden Markov model algorithm procedures.

我们解决八数码问题,广度优先搜索可能会导致内存不够用,采用启发式搜索,启发函数为f(x)=g(x)+h(x) g(x)为该结点不同于目标结点的个数,h(x)为该结点的深度,选择那f(x)结点最小的那个结点进行扩展, 引入了一个"扩展数组[4]"(因为扩展的结点最多只有4个),该数组保存着某个结点的0点向各个方向的扩展的结点对象,然后对该扩展数组进行分析,利用启发函数在进行递归扩展... -us solve eight digital, BFS may lead to insufficient memory, using heuristic search, heuristic function f (x) = g (x) h (x) g (x) for the target node is different from the number of nodes, h (x) for the nodes of depth, the choice between f (x) nodes that the smallest node expansion. the introduction of an "expanded array [4]" (because the expansion of the nodes at most four), The array maintains a node of 0:00 a.m. to expand in all directions in the target node, and then expanded array analysis, use heuristic function during recursive expansion ...