mimo

模糊滑模控制的matlab仿真，希望对大家有用(Fuzzy Sliding Mode Control of matlab simulation, in the hope that useful to everybody)

说明：  文档中包含多个MATLAB函数索引（中英文字母）以及一部分信号处理常用函数(Document contains several MATLAB function index (in English letters) and some of the commonly used signal processing functions)

基于高斯混合模型的情感识别算法 matlab (Hmm emotion recgonition )

说明：  基础的AOA角度估计算法，MUSIC算法，适用于均匀阵列(Basic AOA Angle Estimation Algorithms, MUSIC Algorithms, Suitable for Uniform Arrays)

dv-hop算法,无线传感器网络定位算法(dv-hop algorithm, wireless sensor network localization algorithm)

无功功率补偿器的完整仿真模型，补偿效果通过了验证(The complete simulation model of the reactive power compensator )

维纳滤波程序，给正弦波信号加入信噪比为20dB的高斯白噪声。(Wiener filtering process, to add a signal to the sine wave signal to noise ratio of 20dB Gauss white noise.)

这个是语音增强里面的基本谱减法程序，可以直接编译运用，效果显著(This is the voice inside to enhance the basic spectral subtraction procedures, the compiler can directly use the results significantly)

说明：  里面有关于matlab图像处理的函数的详细介绍和例子。(There are on the matlab image processing function of the detailed introduction and examples.)

共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数(Conjugate Gradient method (Conjugate Gradient) is between the steepest descent method between Newton method and a method, it only USES a derivative information, but overcome the steepest descent method slow convergence of weakness, but also avoid the Newton law needs to storage and computing Hesse inverse matrix and shortcomings, Conjugate Gradient method is not only solve linear equations with most of the large method, and also one of the most effective solution large nonlinear optimization of one of the algorithm. In all kinds of optimization algorithm, the conjugate gradient method is very important. Its advantage is the storage capacity needed, it has small step convergence, high stability, and doesn t require any exotic parameters numerical experiment, this is the modern scientific computing of the answer above problem sets)