很好的边缘检测源代码，使用vc++6.0编写，主要用于医学图像的边缘检测...

经典的BPN人工神经网络例子源码 ，很经典的-BPN classic examples of artificial neural network source code, it is classic

宽度优先搜索法见cpp1.cpp文件，在vc6.0环境运行实现-width priority search see cpp1.cpp documents in the operation to achieve environmental vc6.0

利用matlab编写的神经网络算法，经过测试速度快效果好。-Prepared using matlab neural network algorithm, tested the effect of a good speed.

LIBSVM源码。LIBSVM 是台湾大学林智仁(Chih-Jen Lin)博士等开发设计的一个操作简单、 易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、 n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ） 等问题，提供了线性、多项式、径向基和S形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。-LIBSVM source. LIBSVM is林智仁Taiwan University (Chih-Jen Lin) Dr. develop design a simple, easy to use, fast and effective generic SVM software package, can solve the classification problems (including the C-SVC, n- SVC), regression ( including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and so on, provides a linear, polynomial, radial basis function and the S-shaped kernel function of four commonly used for selection, can effectively to solve a wide range of issues, cross-validation to choose the parameters of the imbalance in the weighted sample, multi-category probability estimation.

人工智能中一个关于野人过河的小程序-AI Savage cross the river on a small procedure

本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值。随代码还提供帮助文件，非常方便。-BP algorithm Demonstration Program, which Levenberg-Marquardt algorithm has practical value. With the code also provides help files, a very convenient.

我的文件是用VC设计的一个求解人工智能中8数码问题的程序。-my VC document is designed to solve a digital AI 8 issue procedures.

C++实现神经网路的bp算法，初学者可以参考下 BP algorithm of neural network s achievement based on c++, maybe it is useful to a new learner-C++ Realization of bp neural network algorithm, beginners can refer to under the BP algorithm of neural network s achievement based on c++, Maybe it is useful to a new learner

bp神经网络识别数字，可识别0-9的十个数字-the number of bp neural network can identify the ten figures 0-9

用java编写的基于小生境的遗传算法，NASG-II，对于用java的朋友来说绝对是个好东西！-Prepared by using java-based niching genetic algorithm, NASG-II, for the friends with java is definitely a good thing!