simpgdsearch

说明：  在matlab平台下，用GA对的lssvm的参数进行优化，很有用的东西。(Platform in matlab, using the GA to optimize parameters lssvm, very useful things.)

RELIABLE automatic recognition of persons has long been an attractive goal. As in all pattern recognition problems, the key issue is the relation between inter-class and intra-class variability:

说明：  Matlab课件，简单实用，对于写论文和做仿真的同学很有用(Matlab)

VBLAST源代码！ 下载后将.rar去掉，即可！ 文件也可用ultraedit等软件直接打开(VBLAST source code! After downloading. Rar removed can be! Documents available ultraedit software directly open)

Krivenko filter bank for glucose purposes

用于主成分分析的源码，由例子可以直接了解PCA的步骤方法(Principal component analysis of the source code used by the example of the method can be directly aware of the steps of PCA)

基于matlab的hmm语音实验平台，包含了众多的实验程序，为语音识别工作提供参考(Matlab-based the hmm Voice experimental platform, contains a large number of experimental procedures, and provide a reference for the voice recognition work)

用matlab作非线性最小二乘拟合，数学建模与数学实验(Using matlab for nonlinear least squares fitting, Math Modeling and Experimental Math)

一种改进的萤火虫算法解决动态0-1背包问题。经过测试，算法就有良好的性能。(Firefly Algorithm (FA), Genetic Algorithm (GA) and Differential Evolution (DE) have been widely used for static optimization problems, but the applications of those algorithms in dynamic environments are relatively lacking. In the present study, an effective FA introducing diversity with partial random restarts and with an adaptive move procedure is developed and proposed for solving dynamic multidimensional knapsack problems. To the best of our knowledge this paper constitutes the first study on the performance of FA on a dynamic combinatorial problem. In order to uate the performance of the proposed algorithm the same problem is also modeled and solved by GA, DE and original FA. Based on the computational results and convergence capabilities we concluded that improved FA is a very powerful algorithm for solving the multidimensional knapsack problems for both static and dynamic environments.)

人工蜂群算法matlab源程序，实现利用蜂群算法最优化问题(artificial bee colony algorithm)