人工神经网络，利用matlab工具箱算法

利用pso算法训练人工神经网络的源代码。-PSO algorithm for the use of training artificial neural network source code.

求解tsp问题的模拟退火源码，数据文件请仿照文件中的input.txt自行创建-the simulated annealing source, data files copied documents requested the creation of their own input.txt

美国麻省理工学院出的遗传算法方面的好书.-Massachusetts Institute of Technology in the United States out of aspects of genetic algorithms books.

　人工神经网络(Aartificial Neural Network，下简称ANN)是模拟生物神经元的结构而提出的一种信息处理方法。早在1943年，已由心理学家Warren S.Mcculloch和数学家Walth H.Pitts提出神经元数学模型，后被冷落了一段时间，80年代又迅猛兴起［1］。ANN之所以受到人们的普遍关注，是由于它具有本质的非线形特征、并行处理能力、强鲁棒性以及自组织自学习的能力。其中研究得最为成熟的是误差的反传模型算法(BP算法，Back Propagation)，它的网络结构及算法直观、简单，在工业领域中应用较多。-Artificial Neural Networks (Aartificial Neural Network, under the short title of ANN) is a simulation of the structure of biological neurons and the information put forward a method of treatment. At early 1943, by Warren S. Mcculloch psychologists and mathematicians Walth H. Pitts proposed mathematical model of neurons, was left out in the cold for some time, and the rapid rise of the 80" s [1]. ANN because the general concern of the people is the essence of it is because of the non-linear characteristics of parallel processing capabilities, strong robustness and self-organizing capacity of self-learning. Research one of the most sophisticated are the error-propagation model of the algorithm (BP algorithm, Back Pro

这是一个关于目前最前沿课题的神经网络学习模型的程序-xor-This is a topic on the forefront of the current neural network learning procedures for model-xor

程序代码说明 神经网络的实例,内附详细说明-Code description examples of neural network, containing a detailed description of

一个神经网络原型代码，针对的例子为《Perceptron Learning》 (Russell & Norvig， 第742页)-A neural network prototype code, for example for

计算欧几里德距离C语言源代码,次源码经测试可有效运行,源码简单易懂-Calculation of Euclidean distance C-language source code, sub-source has been tested and can be effectively run, easy-to-read source

对支持向量机进行训练的一种改进的遗传算法。-On support vector machine for training an improved genetic algorithm.

John Wiley & Sons,.Fuzzy Engineering Expert Systems with Neural Network Applications.[2002.ISBN0471293318]