这是关于MATlab的一个PDF文档，这个文档清晰的给出了 Matlab的使用方法...

duobinary conversion for agiven input symbols

线性方程组，非线性方程组，最小二乘拟合等数值算法的matlab实现。(Linear equations, nonlinear equations, numerical algorithm such as least-squares fitting of the realization of matlab.)

ICA独立分量分析，通过协方差白化，熵编码算法。(ICA, through covariance albino, entropy coding algorithm.)

matlab定点仿真资料，介绍如何用matlab进行定点仿真，便于下一步的硬件仿真(Matlab fixed-point simulation data)

Matlab实现界面友好，非归零型差分相位调制信号建模与仿真分析 ，线性调频脉冲压缩的Matlab程序,通过matlab代码，相参脉冲串复调制信号，与理论分析结果相比。( Matlab to achieve user-friendly, NRZ type differential phase modulation signal modeling and simulation analysis, LFM pulse compression of the Matlab program, By matlab code, Complex modulation coherent pulse train signal, Compared with the results of theoretical analysis.)

里面有DAB常见的SPS控制，EPS控制，DPS控制，可供DAB的初学者学习使用(There are DAB common SPS control, EPS control, DPS control, which can be used by beginners of DAB.)

基于峭度的盲分离开关算法的matlab源代码程序(Blind Source Separation Based on Kurtosis switch algorithm )

The optimization behavior of the self-adaptation (SA) evolution strategy (ES) with intermediate multirecombination (the (=I )-SA-ES) using isotropic mutations is investigated on the general elliptic objective function. An asymptotically exact quadratic progress rate formula is derived. This is used to model the dynamical ES system by a set of difference equations. The solutions of this system are used to analytically calculate the optimal learning parameter  . The theoretical results are compared and validated by comparison with real (=I )-SA-ES runs on typical elliptic test model cases. The theoretical results clearly indicate that using a model-independent learning parameter  leads to suboptimal performance of the (=I )-SA-ES on objective functions with changing local condition numbers as often encountered in practical problems with complex fitness landscapes.

WAVELET CODING FOR IMAGE

《压缩感知与应用》源代码，包含SAR图像压缩感知、高光谱压缩感知、基于结构稀疏的SAR图像低秩重建( Compressed sensing and application source code, including SAR image compressive sensing, hyperspectral image compression, based on the structure of sparse SAR image low rank reconstruction)