ROMP

MATLAB 下的LDPC编码解码，自己编写，在7/0下通过验证(Decoding LDPC codes under MATLAB, I have written, in 7/0, validated)

关于MATLAB的基本使用的另个程序，主要关于图像处理的(The basic use of MATLAB on the other two procedures, mainly on image processing)

AirSWOT JPL s Earth Science Airborne Program scacacascassssssssssssssssca

Boundary Integral Method Code

多抽样率信号处理，最大似然（ML）准则和最大后验概率（MAP）准则，一种噪声辅助数据分析方法,考虑雨衰 阴影 和多径影响，鲁棒性好，性能优越，使用大量的有限元法求解偏微分方程。( Multirate signal processing, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, A noise auxiliary data analysis method, Consider shadow rain attenuation and multipath effects Robustness, superior performance, Using a large number of finite element method to solve partial differential equations.)

说明：  数学建模涉及到的算法大全，书中包含有介绍以及算法，对于建模爱好者是有非常大的好处。(Mathematical modeling related to the algorithm Daquan, the book contains a description, as well as algorithms for modeling enthusiasts there is a very big advantage.)

利用PID控制算法实现曲线的拟合跟踪，分别对阶跃曲线和正弦曲线进行控制，并比较拟合的误差曲线(Using the PID control algorithm curve fitting tracking, respectively, on the step and sinusoidal curve control, and compare the error curve fitting)

fit_ML_normal - Maximum Likelihood fit of the log-normal distribution of i.i.d. samples!. Given the samples of a log-normal distribution, the PDF parameter is found fits data to the probability of the form: p(x) = sqrt(1/(2*pi))/(s*x)*exp(- (log(x-m)^2)/(2*s^2)) with parameters: m,s format: result = fit_ML_log_normal( x,hAx ) input: x - vector, samples with log-normal distribution to be parameterized hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields m,s - fitted parameters CRB_m,CRB_s - Cram?r-Rao Bound for the estimator value RMS - RMS error of the estimation type - ML

说明：  （蒙特卡洛方法） 求出四分之一圆占正方形的比例。随机投点P(x,y)于正方形，π/4的近似值为落在四分之一圆内的点数与总投点数的比值。随机投点次数分别为10000次和50000次，计算π的近似值。 ((Monte Carlo method) are obtained accounting for a quarter of a round square ratio. Voted random point P (x, y) in the square, π/4 for the fall quarter of the approximation of the points won and the ratio of the total vote points. The number of random points, respectively, voted for the 10000 and 50000 times, the calculation of the approximation of π.)

用matlab中gui做一个普通的科学计算器,可以参考一下(through Matlab gui，a common scientific calculator was made , you can consult it)