小程序

粗糙集matlab算法，有属性约简，值约简，规则生成等多种算法。(Neighborhood rough set based feature evaluation and reduction)

说明：  MATLAB s symbolic features to derive Simpson s 1/3 integration rule

说明：  基于支持向量机和模糊系统的机器学习方法及其应用研究 文档 写的很好(SVM Fuzzy SYSTEM )

A new method for periodic scattering problems using 2nd kind boundary integral equations and the free-space Green s function, adding extra degrees of freedom on the unit cell walls, and imposing quasi-periodicity in an expanded linear system.(A new method for periodic scattering problems using 2nd kind boundary integral equations and the free-space Green s function, adding extra degrees of freedom on the unit cell walls, and imposing quasi-periodicity in an expanded linear system. This avoids the problems with the standard approach, namely: the quasi-periodic Green s function is slow to evaluate, it diverges at Wood s anomalies, and it does not handle large aspect ratios well. Our new approach cures all three issues, and can easily be `wrapped around an existing code (e.g. fast-multipole acceleration) for the isolated-obstacle scattering problem. It includes the latest talk slides: "A new integral representation for quasi-periodic scattering problems in two dimensions")

国外网站下载的程序包，包含mindist_classifier_type，pca，PNN，svm等几个算法程序，希望对大家有用。(Foreign website package, including mindist_classifier_type, pca, PNN, svm algorithm program, and several, we hope to be useful.)

典型的量子遗传算法，求解最值问题,绝对没有密码(The typical quantum genetic algorithm is the most value problems)

一个SM和STBC的代码，matlab编写，可是实现任意qam调制，可以计算误码率(A SM and STBC code, matlab prepared, but the realization of arbitrary QAM modulation, bit error rate can be calculated)

iradon1 function with matlab

一个身体部位比较模型的新方法网络（BAN）的，可以容纳多个环节和多个科目。所述的绝对测量允许跨频谱可能刻画的比较 从单参数为整个合奏，通过基于参数化到每个活动，每个学科和每个环节模型。使用错误，并明确之间权衡复杂性，在一个善良的适应措施相结合，显示有重要的影响时，适用于一系列典型的禁止通道数据。它是有不同的 在模式的选择的影响，以及它相关的复杂性，混合活动的“日常”的数据，设置活动相比，动态数据（例如步行）。平均路径损耗的不足，甚至位数的路径损失的措施，作为唯一的表征还强调“禁止通道。 (A new approach to compare models for body area networks (BAN) that accommodates multiple links and multiple subjects is presented. The absolute measure described allows comparison across a spectrum of possible characterizations ranging from single-parameter for an entire ensemble, through to per-activity, per-subject and per-link based parameterized models. The use of an explicit trade-off between error and complexity, combined in a goodness-of-fit measure, is shown to have important consequences when applied to a range of typical BAN channel data. It is shown that there are different implications in choice of model, and it’s associated complexity, for mixed-activity “everyday” data, when compared with set-activity dynamic data (e.g. walking). The deficiency of mean path loss, or even median path loss measures, as a sole characterization of the BAN channel is also highlighted.)

遗传算法求函数极大极小值，可用于简单的最优控制(Genetic algorithms function Minimax, optimal control for simple)