PID-matlab

功率谱估计，通过matlab程序对声发射信号进行功率谱估计(Power spectrum estimation, through the matlab program to acoustic emission signals, power spectrum estimation)

MIMO Capacity Matlab s code

This book is an introduction to two subjects:Matlaband numerical computing. This first chapter introducesMatlabby presenting several programs that inves- tigate elementary, but interesting, mathematical problems. If you already have some experience programming in another language, we hope that you can see how Matlabworks by simply studying these programs.

实现了零速修正的卡尔曼滤波算法，可实现个人室内导航。为读数据格式(Zero speed correction Kalman filter algorithm can achieve personal indoor navigation. Read data format)

说明：  通过模型预测控制（MPC）对单相逆变器进行电流跟踪控制(Current tracking control of single-phase inverter by MPC)

详细介绍程序的编写步骤,并且附有原代码.是一个横好的matlab程序．(Introduce procedures for the preparation of detailed steps, and with the original code. Is a good cross-matlab procedures.)

不用多说了，和Hogh搭配使用检测直线的程序 直线Hough变换利用图像空间和Hough参数空间的点－线对偶性，把图像空间中的检测问题转换到参数空间。通过在参数空间里进行简单的累加统计，然后在Hough参数空间寻找累加器峰值的方法检测直线。(Needless to say, Hogh mix and the use of linear detection procedures Hough transform space and the use of images Hough parameter space The point-line duality, the image space detection switch to the parameter space. Through the parameter space for a simple cumulative statistics, then Hough parameter space for accumulator peak detected straight.)

可见光通信中，采用OOKNRZ调制方式时的系统误码率，自己跑过，没问题的。(BER of OOKNRZ in visible light communication system)

这是关于脑电信号预处理的程序，希望对大家有帮助(This is about the brain electrical signal preprocessing procedure, I hope it can help you)

针对SVM法线特征筛选算法仅考虑法线对特征筛选的贡献,而忽略了特征分布对特征筛选的贡献的不足,在对SVM法线算法进行分析的基础上,基于特征在正、负例中出现概率的不同提出了加权SVM法线算法,该算法考虑到了法线和特征的分布.通过试验可以看出,在使用较小的特征空间时,与SVM法线算法和信息增益算法相比,加权SVM法线算法具有更好的特征筛选性能.(Normal feature selection for SVM algorithm only considered normal for the contribution of feature selection, to the neglect of the characteristics of the distribution of feature selection have contributed to the lack of normal SVM algorithm based on the analysis, based on the characteristics of the positive and negative cases emergence of a different probability-weighted normal SVM algorithm, which takes into account the distribution and characteristics of normal. through the test can be seen in the use of smaller feature space, the normal and the SVM algorithm and information gain algorithm, normal weighted SVM algorithm has better performance of feature selection.)