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matlab的一些图像处理的例子和讲解，适合习惯于用matlab画图的人使用(something about matlab)

MAPPED WENO SCHEME FOR EULER EQUATIONS

this is one of the best satelite code in the world to find the look angle

16QAM盲均衡,恒模算法，400次仿真，做出星座图，误差曲线(blind equalizaton for 16QAM,constant modulus algorithm，realization 400times ,constellation ,mmse curve)

解相干的MUSIC算法，用于阵列信号处理(Decorrelation MUSIC algorithm for array signal processing)

这段代码利用分步傅里叶方法求解非线性薛定谔方程的matlab程序(This code solves the NLS equation with the split-step method)

Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sensed speech. Since the linear transform is signal dependent and unknown, unlike the standard CS formulation, a codebook of transfer functions is proposed in a matching pursuit (MP) framework for CS recovery. It is found that MP is efficient and effective to recover CS encoded speech as well as jointly estimate the linear model. Moderate number of CS measurements and low order sparsity estimate will result in MP converge to the same linear transform as direct VQ of the LP vector derived the original signal. There is also high positive correlation between signal domain approximation and CS measurement domain approximation for a large variety of speech spectra.

In mathematics, the Fibonacci sequence is the following infinite sequence of natural numbers: The first element is 0, the second is 1 and each remaining element is the sum of the previous two: Each element of this sequence is called Fibonacci number. This sequence was described in Europe by Leonardo of Pisa, XIII century Italian mathematician known as Fibonacci. It has numerous applications in computer science, mathematics and game theory.

求解线性规划问题，简单的求解以及多远线性规划的求解，(To solve the linear programming problem solving and simple, how far solution of linear planning )

说明：  计算表面粗糙度高斯分布，利用matlab采取扫描方法(Calculation of Gaussian distribution of surface roughness)