特征提取技术。这种技术以传统的建模方式为前提，对于产生的模型的几何、拓扑等信息加以分析以提取其特征信息，这种技术一般多采用人工智能及模式识别等方面的知识。...

本程序是人工编写的bp神经网络，针对识别样本btw三类进行训练和识别。-This procedure is prepared bp artificial neural networks, btw samples for identification of three types of training and identification.

本书介绍了一些关于机器人的识别技术，值得学习和借鉴，作为基础资料不错-The book introduced a number of robot recognition technology, it is worth to learn from, as a good basis for information

利用神经网络预测时间序列，以太阳黑子和实际的转子故障信号为例，matlab编程-Using neural network time series prediction to sunspots and the actual rotor fault signal as an example, matlab programming

University of Amsterdam的2003年robocup源程序代码，队名trilearn，老牌2D强队-University of Amsterdam

该程序是基于MATLAB环境的pso实现tsp问题-The program is based on the MATLAB environment, the issue of PSO realize tsp

企业竞争力关键决定因素的直觉模糊识别模型，值得借鉴-competitiveness of enterprises key determinants of intuition fuzzy recognition model, worth learning

RBF实现神经网络预测程序，压缩包，不用解压缩密码！-Realize RBF neural network prediction program, compressed packet, do not extract the password!

神经网络C语言源程序 绝对经典。 ADALINE,ART1,BAM,BOLTZMAN,BPN CPN,hopfield, som, -neural network C language source absolute classic. ADALINE, ART1, BAM, BOLTZMAN, CPN 7.82, hopfield, som.

classification_matlab_toolbox分类方法工具箱，有界面很直观。-classification_matlab_toolbox classification toolbox, a very intuitive interface.

　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