wideband

说明：  图像在传输或长期保存中会存在图像质量下降，此程序用来对此类图像进行复原(Image in a transmission or long-term preservation will exist in image quality drop, the program used to such image restoring)

This program has been written using Matlab/Simulink software. It can be used to find out the behavior of the induction motor behaviore when fed from a PWM inverter. The program is written so that the user can simulate any induction motor he wants by just loading the electrical and the machanical parameters in the workspace. The induction motor is modelled by the 7th order dq model which takes the iron loss component into account. The motor works in open loop but the closed loop can be easly performed by just adding the vector controller or any other controller and a PI speed controller.

A matlab code which calculates the velocity profile for a flow in a 2d channel using the lattice boltzmann method.

Voice recognition LPC VS MFCC with K-NN

Input-Output Time-Series Prediction, Forecasting, Dyanamic modelling Nonlinear autoregression, System identification and Filtering

最短路分配方法流程图的matlab编码（全有全无配流法）(The shortest path distribution method)

极化码研究论文 仿真 分析 编码 解码 原理介绍 背景介绍 (Polarization code simulation analysis research paper describes the principles codec Background)

matlab实现hough变换直线提取，不直接用hough算子，应用二值化图像(to achieve a straight line hough transform matlab extraction, does not directly hough operator, the application of binary image)

实现各阶本原多项式的小m序列的长生，通过改变本原多项式的生成矩阵可以产生想要的m序列的(Order to achieve the small-m primitive polynomial sequence longevity, by changing the primitive polynomial generator matrix m can produce the desired sequence)

独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S + N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...( Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S+ N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...)