B.TECH-PROJECT-PRESENTATION

实现图像的游程编码，有示例，希望大家喜欢(The run-length encoding of image, there are examples, I hope you like)

采用matlab编程用以实现各种常见离散序列的生成(Discrete Sequence)

The Wavelet Decomposition And Reconstruction Based on The Matlab

说明：  高光谱分析工具,常用的函数matlab实现(hyperspetral tool)

MATLAB优化算法案例分析与应用.pdf，余胜威所著，高清电子书，全本(MATLAB Optimization Case Analysis and Application .pdf, Yu Shengwei book, e-book definition, all of the)

驻波 行波 行驻波演示M文件,经调试，运行良好(the M.file of performing standing wave &travelling wave &standing-travelling wave)

计算求解连续时间信号的SINAD，分析其频谱特型(Calculate the SINADof Real Signal)

一个简单的例程，对仿真信号使用RLS算法进行自适应滤波(A simple routine of simulated signals using RLS adaptive filtering algorithms)

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...)

MATLAB实现声音信号的小波分解与重构（内副数据）(MATLAB voice signals in the wavelet decomposition and reconstruction (with Vice data))