基于VC开发的一个神经网络源程序,与大家共享

神经网络中的感知机的学习算法的c语言程序源代码-neural network of Perceptron learning algorithm in C language source code

Libsvm - MATLAB version-Libsvm- MATLAB version

多目标跟踪 (三维)-算法matlab编制-multi-target tracking (3D)- preparation algorithm Matlab

英国Sheffield大学遗传算法函数包，可节省遗传算法函数开发-Sheffield University United Kingdom function genetic algorithm package, can save the development of genetic algorithm function

围绕粒子群的当前质心对粒子群重新初始化.这样，每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”（wvi）向Pi，Pg的方向前进，从而可以在粒子群的运动过程中获得新的位置，增加求得更优解的机会.随着迭代的继续，经过变异的粒子群又将趋向于同一点，当粒子群收敛到一定程度时又进行下一次变异，如此反复，直到迭代结束.-particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.

用遗传算法实现任务分配优化的源程序。-genetic algorithm optimization task allocation of the source.

遗传算法方法，步骤，实例。详细，有实例，很不错。-Genetic algorithm methods, steps, examples. Detail, there are examples of very good.

用高斯和离子滤波来跟踪视频图像中的移动对象，和模式识别有关-And ions with Gaussian filtering to track video images of moving objects, and pattern recognition on the

1。《遗传算法的数学基础》，张文修、梁怡编着 西安交通大学出版社 2000年第一版 遗传算法（genetic algorithm）是模拟自然界生物进化过程与机制求解问题的一类自组织与自适应的人工智能技术，已广泛应用于计算机科学、人工智能、信息技术及工程实践。 本书重点在于阐述遗传算法的数学基础。全书共分3章，第1章给出了遗传算法的几何理论，第2章给出了遗传算法的马尔可夫链分析，第3章给出了遗传算法的收敛理论。 本书可以作为应用数学、计算机科学、系统科学等专业研究生的教材，也可以作为研究遗传算法的参考书。 -1. "Genetic Algorithm mathematical basis," Zhang Xiu, Yi Liang compile Xi"an Jiaotong University Press in 2000 the first edition of the genetic algorithm (genetic algorit hm) is a simulation of natural biological evolution process and mechanisms to solve the problem of a kind of self-organization and adaptive artificial intelligence technology, has been widely used in computer science, artificial intelligence, information technology, and engineering practice. The book focused on the genetic algorithm described math. The book is divided into three chapters, one chapter is a genetic algorithm of the geometric theory Chapter 2 of the genetic algorithm is a Markov chain analysis, presented in Chapter 3 of the geneti

用遗传算法优化神经网络权值的源程序-genetic algorithm optimization neural network value of the source