基于java实现的遗传算法 神经网络 实数编码 交叉 选择 变异

实现文字的识别 利用比较先进的神经网络笔者已经实验 绝对可行！-it is a good method to realize te recgniton of words.it is based on bp network,the author realized it!

遗传算法的c语言程序-Genetic Algorithm c Language Program

mtlab的遗传算法的源程序,很好用的,这是个压缩文件,请解压缩后使用-mtlab genetic algorithm source, the good, it is a compressed file, decompress after use

The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application.-The software implements particle filteri Vi and Rao Blackwellised particle filtering az r conditionally Gaussian Models. The RB algori thm can be interpreted as an efficient stochast ic mixture of Kalman filters. The software also includes efficient state-of-the-art resampl ing routines. These are generic and suitable az r any application.

基于自组织特征映射网络的聚类分析，是在神经网络基础上发展起来的一种新的非监督聚类方法，分析了基于自 组织特征映射网络聚类的学习过程，分析了权系数自组织过程中邻域函数和学习步长的一般取值问题，给出了基于自组织 特征映射网络聚类实现的具体算法，并通过实际示例测试，证实了算法的正确性。 -Based on self-organizing feature map network cluster analysis, neural network is developed on the basis of a new non-supervised clustering method, analysis based on self-organizing feature map network clustering of the learning process, analyzed the weights of self-organization the process of neighborhood function and learning step-size problem of the general values are given based on the self-organizing feature map network clustering algorithm to achieve concrete and practical examples of tests, confirmed the correctness of the algorithm.

ICA经典文章,入门必看。受益，高阶矩统计牲在信号处理中的应用，详细介绍许多重要概念。-ICA classic article, the entry Watchable. Benefit Higher Moments statistical offerings in signal processing applications, detailed many important concepts.

基于感知器神经网络处理复杂的分类问题-based perceptron neural network to handle complex classification problems

BOLTZMAN（vc＋＋编写的程序神经网络程序）

模糊技术与神经网络技术选编-fuzzy and neural network technology Selected