question4

说明：  常见的图像处理matlab源代码！！包括反色，常见滤波，去噪，和常用变换！(common image processing Matlab source code! ! Anti- including color, common filtering, noise removal, and common Transform!)

介绍了一种代数过完备ICA算法，采用这种方法对混合语言信号进行分解。(Algebraic independent component analysis an approach for separation of overcomplete speech mixtures)

该工具箱包括了二种分类,二种回归,以及一种一类支持向量机算法 (1) Main_SVC_C.m --- C_SVC二类分类算法 (2) Main_SVC_Nu.m --- Nu_SVC二类分类算法 (3) Main_SVM_One_Class.m --- One-Class支持向量机 (4) Main_SVR_Epsilon.m --- Epsilon_SVR回归算法 (5) Main_SVR_Nu.m --- Nu_SVR回归算法(The kit includes two kinds of classification, two kinds of regression, and a one-class support vector machine algorithm (1) Main_SVC_C.m--- C_SVC II classification algorithm (2) Main_SVC_Nu.m--- Nu_SVC II classification algorithm (3) Main_SVM_One_Class.m--- One-Class Support Vector Machine (4) Main_SVR_Epsilon.m--- Epsilon_SVR regression algorithm (5) Main_SVR_Nu.m--- Nu_SVR regression algorithm)

the code is to track the lips. which need to be marked by red color. the code tracks the red color of the lips and thus the lips indirectly. such system can be very much useful for audio visual departments

matlab仿真的频率捷变雷达信号，进行了时域显示和脉压分析，适用于对雷达信号处理学习的同学。(matlab simulation of frequency-agile radar signals for display and pulse time-domain analysis for radar signal processing for the students to learn.)

L-M(Levenberg—Marquardt)是一种非线性最优化里面最常用的方法之一，改方法能快速而准确的逼近收敛值。本文简述了改方法的操作原理和具体运用，如可以方便的用于有约束与无约束最优化的求解。本文件里面有源码和测试码以及对该方法的具体介绍PDF文件。欢迎下载。(L- M (Levenberg- Marquardt) is a kind of nonlinear optimization inside one of the most commonly used method, change method can fast and accurate approximation convergence value.This paper briefly describes the operating principle of change method and concrete application, such as easy to solve constrained and unconstrained optimization.This document there are source code and test code as well as to the PDF file the detailed introduction of the method.Welcome to download.)

压缩感知程序源码，Blind compressed sensing (BCS)不需要在采样和恢复阶段预先知道稀疏基。源码对于研究压缩感知前沿具有很好的借鉴意义。(The fundamental principle underlying compressed sensing is that a signal, which is sparse under some basis representation, can be recovered from a small number of linear measurements. However, prior knowledge of the sparsity basis is essential for the recovery process. Blind compressed sensing (BCS) avoids the need to know the sparsity basis in both the sampling and the recovery process. That is, BCS aims at recovering an ensemble of vectors, all sparse under the same unknown basis, given small number of linear measurements of these vectors. )

signal processing: downsampling/upsampling a signal and using of ZOH.

matlab/simulink中电池模型的使用和数据采集(matlab/simulink model used in batteries and data acquisition)

For Plotting in matlab