基于熵函数的语音端点检测方法.rar格式为ｖｉｐ

这是用VC编程实现模糊控制来控制机器人的运动-The misty control imitate really

人工智能课程中关于产生式系统部分上机实验的源代码，有很大参考价值。-No

KNN和BP的算法实现。输入一系列的样本值，进行训练和分类。源码是实现了两个分类器，已经调试通过-KNN and BP algorithm. Enter a series of sample values, for training and classification. Source is to achieve the two classifiers have been debugging through

模式识别下的ISODATA算法 例子为IRIS数据库数据-ISODATA algorithm for pattern recognition under the examples for the IRIS database data

有关TSP遗传算法的的三个pdf论文。不错的参考-The TSP of the three genetic algorithms pdf papers. A good reference

文本分类算法很多，神经网络算法遗传算法可以用，本算法采用支持向量机SVM来实现-Text Classification Algorithm

FastICA算法,使用matlab语言,是非常好的独立成分分析工具.-Fast algorithm, using Matlab language, is a very good independent component analysis tools.

模拟退火算法 模拟退火算法(Simulated Annealing,简称SA算法)是模拟加热熔化的金属的退火过程，来寻找全局最优解的有效方法之一。 模拟退火的基本思想和步骤如下： 设S＝{s1,s2,…,sn}为所有可能的状态所构成的集合， f：S―R为非负代价函数，即优化问题抽象如下： 寻找s*∈S，使得f(s*)＝min f(si) 任意si∈S （1）给定一较高初始温度T，随机产生初始状态S （2）按一定方式，对当前状态作随机扰动，产生一个新的状态S’ S’＝S＋sign(η).δ 其中δ为给定的步长， η为[－1,1]的随机数-simulated annealing algorithm (Simulated Annealing, or SA algorithm) is a simulation of heating molten metal in the annealing process, to find the global optimum one of the effective ways. Simulated Annealing basic ideas and the steps are as follows : S = (s1, s2, ..., sn) for all possible state posed by the pool, f : S-R non-negative cost function, that is abstract optimization problems are as follows : Find S* s, making f (s*) = min f (si) arbitrary si S (1) to set a higher initial temperature T, randomly generated initial state S (2) of a certain form, the current state of random disturbance, have a new state S "S" = S+ sign (). delta where given for the step, [-1,1] Random Number

Dynamic Programming Code for the TSP

神经网络与遗传算法结合，需要的朋友就不用多说了，仅供学习和参考。-Neural network and genetic algorithm combined with the need for friends goes without saying, for learning and reference.