一个机器人信息显示系统，代码比较全，你会喜欢的

编程的 BP算法并行,很好,值得下载,详细的介绍了BP算法-Of the BP algorithm for parallel programming, well worth downloading and detailed description of the BP algorithm for

用VC编制的集成的野人和八数码演示程序。其中野人程序用动态的效果演示，并能设置进度。八数码程序能根据给出的源状态转换成目标状态。-VC establishment of integrated Savage and eight digital presentations. Savage procedures which use dynamic demonstration effect, and can be programmed to progress. Eight digital process according to the source is converted into a state target state.

关于遗传算法编成的一本书，有遗传算法基础的人看。较权威的一本书-On the genetic algorithm into a book, a genetic algorithm-based perspective. Than the authority of a book

使用anfists的sugeno-type对混沌时间序列预测。-the use anfists Sugeno-type of chaotic time series prediction.

遗传算法解决NN逼近任意函数-genetic algorithm to solve arbitrary function approximation NN

采用贝叶斯正则化算法提高 BP 网络的推广能力。我们采用两种训练方法，即 L-M 优化算法（trainlm）-?捎??

基于VC++的小波提升程序，包含小波提升的详细算法。对初学者有很大帮助-Based on VC++ The Wavelet Lifting procedures, including detailed algorithm Wavelet Lifting. Have a great help for beginners

简单的遗传算法源代码，挺实用的，大家可以借鉴-Simple genetic algorithm source code, very useful, we can learn from

内附两个源代码，其中一个源代码是识别程序的，另一个是一个矩阵类库的，所以一并附上。 ~..~因为已经保存了训练好的网络权值，所以第一次使用识别程序时，可以直接运行Release目录下的可执行文件，然后对图片目录中的测试图片进行读入、识别。 当然读者也可以自行用训练样本训练网络，不过要特别注意训练样本的选择，否则可能造成识别率很低。训练样本选择的原则是，尽可能的有代表性，在训练时间不至于太长的情况下，训练样本数目尽量多。 -containing 2 source code, which is a source identification procedures, and the other is a matrix class library. So accompanied. ~ ~ .. Has been preserved because of the trained network weights, the first use of the identification procedures, can be run directly Release directory executable file, Then the catalog of tests conducted read into the picture, recognition. Certainly readers can use their own training samples training network, but special attention should be paid to the choice of training samples, Otherwise, it could cause a very low recognition rate. Training sample selection principle is that as far as possible be representative, in the training of the time not too long under the circumstances, the number of training samples as much as possible.

针对现有遗传算法在多维非线性优选方面的不足，本文提出了一种基于小生境进化算法（NEA）的非线性优选模型，探讨了NEA算法的参数选择原则。通过大量仿真和比较，表明算法在复杂非线性优选中具有快速、高效、鲁棒性强的特点，并能在全局范围内有效搜索所有最优解。 -against existing genetic algorithms in three-dimensional nonlinear optimization for the shortage, the paper presents a niche evolutionary algorithm (NEA) nonlinear optimization model, the NEA on the parameters chosen algorithm principle. Through simulation and large, the algorithm shown in a complex nonlinear optimization is fast, efficient, robust features of the strong, and the global scope effective search all the optimal solution.