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这是一本进化算法的电子书，很适合人工智能方面的人学习-This is an evolutionary algorithm e-book, it is suitable for artificial intelligence to learn

pso 的一个演示源码，欢迎初学者下载，共同进步-pso source of a presentation, please download beginners, and common progress! ! ! ! ! !

BP算法C++的BP算法源程序 BP算法C++的BP算法源程序 -BP algorithm C BP algorithm source algorithm C BP BP algorithm source code

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.

c语言编写的蚁群算法源程序，应用于TSP-c language source code of ant colony algorithm applied to TSP

matlab环境下，基于云模型的分类器，包括基于例子群优化的云分类器，和属性相似度云分类器。-Matlab environment, based on cloud model for the classification, including examples Swarm Optimization Based on the cloud classifier, and attribute similarity cloud classifier.

目前开发人工只能的朋友一定会遇到bp算法中八进制的问题，这段程序很好的解决了这个问题。我目前在作模糊控制，神经网络，遗传算法的课题，收集了很多相关程序，望同方向者探讨一二。-only friends will find bp algorithm octal problem, this process satisfactorily resolved this problem. Now I make fuzzy control, neural networks, genetic algorithms topic, a lot of collection procedures, and hopes to explore the same direction on January 2.

Eigenface and Fisherface Performance Across Pose

提出了基于最小化估计的泛化误差界非优化估计方法。目前大多数的核参数选择方法都是通过极小化了来得到最优参数值，但是求解优化问题的计算代价相当的大，并且不能很好地体现数据的分布特征。本文采用非优化技术，通过极小化泛化误差来优化核及相关参数，由于直接计算最小半径和最大间隔，避免了对优化问题的直接求解，因此可以很好地降低计算代价。并且该方法直接从样本出发，可以很好地体现数据的分布特征，不管数据分布是否均匀都可以适用。给出了基于凸包估计的SVM核选择的模型及实现算法。 -Proposed based on minimizing the estimated generalization error bound of the non-optimal estimation method. Most of the nuclear parameter selection methods are to get the best by minimizing the parameter values, but the computational cost for solving optimization problems is quite large, and can not properly reflect the distribution characteristics of the data. In this paper, the non-optimization technology, by minimizing the generalization error to optimize the nuclear and related parameters, due to the direct calculation of the minimum radius and maximum interval, avoiding the direct solution of the optimization problem, it can very well reduce the computation cost. And that the method directly from the sample one can well reflect the distribution chara