LS-SVMLab-v1.7

说明：  遗传算法的三种操作代码，差分进化算法(Differential Evolution Algorithm，DE)是一种高效的全局优化算法。它也是基于群体的启发式搜索算法，群中的每个个体对应一个解向量。差分进化算法的进化流程则与遗传算法非常类似，都包括变异、杂交和选择操作，但这些操作的具体定义与遗传算法有所不同(Three operation codes of genetic algorithm)

一种优化算法，用于解决线性反转问题，程序可以直接运行，算法比较精确(An optimization algorithm is used to solve the linear inversion problem. The program can run directly, and the algorithm is more precise.)

基于差分法的QRS波检测算法程序（PAN.J, TOMPKINS. W.J： A Real-Time QRS Detection Algorithm 对应的matlab程序）。(QRS detection algorithm program based difference method (PAN.J, TOMPKINS WJ:. " A Real-Time QRS Detection Algorithm" corresponding matlab program).)

这次上传的代码是关于K-means clusters的代码，希望能对大家有用。(The uploaded code is about K-means clusters.I hope it can be a help to everyone.)

BP网络的MATLAB实现，用BP网络完成函数的逼近，具体见里面的README(BP Network MATLAB, BP network to be completed function approximation, the specific see inside the README)

在介绍非线性动力学现代理论中的混沌理论的基础上 综述了混沌理论及其方法在脑 电 心电及肌电等医学信号处理中的应用 并展望了它们的发展趋势 旨在推进非线性分析方法在生物医学中的研究和应用(In introducing the modern theory of nonlinear dynamics of chaos theory, based on an overview of chaos theory and its method in EEG and EMG and other ECG medical signal processing applications and prospects of their development trends aimed at promoting non-linear Analysis Method in Biology and Medicine Research and Application)

说明：  基于几何统计特征的印鉴自动识别算法 －－－文章(Based on the geometric characteristics of each automatic identification algorithm is based on the geometric characteristics of each algorithm for automatic identification article )

提取人体手臂肌电信号，手势识别，包括肌电信号的预处理，端点检测，特征提取，特征降维，SVM分类识别(sEMG based hand movements recognition using SVM)

说明：  ECG的应用：ECG在医疗检测方面发挥着中重要作用，本文中包含ECG 的Q波检测和ECG的分类，所以，心电信号至关重要。(Application of ECG: ECG plays an important role in medical detection. This paper includes Q wave detection of ECG and classification of ECG, so ECG signal is very important.)

说明：  表面肌电信号数字传感器的设计。表面肌电（suRFace electromyography, sEMG）信号是神经肌肉系统在进行随意性和非随意性活动时的生物电变化经表面电极引导、放大、显示和记录所获得的一维电压时间序列信号，其振幅约为0-5000μV，频率0-1000Hz，信号形态具有较强的随机性和不稳定性。与传统的针式肌电图相比，sEMG的空间分辨率相对较低，但是探测空间较大，重复性较好，对于体育科学研究、康复医学临床和基础研究等具有重要的学术价值和应用意义[1]。(Surface EMG digital sensor design)