Fountain-code

matlab编写的，盲源分离的程序汇总，学习信号处理非常有用(matlab written summary of blind source separation program, learning is very useful signal processing)

4键值频移键控的一个代码示例，可以画出频谱图，可以更改码元长度(4 key frequency shift keying)

k ua gi aegt ae gtaert .a wg.

传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这 一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT) 系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表 示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的 语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法在抑制背景噪声和减少语音失真等方面优 于传统的语音增强方法。(The spectral components of speech are usually assumed to be independent in traditional short-time spectrum estimation, which is not the case in practice. Tosolve this problem, a new speech enhancement algorithm with multivariate Laplace speech model is proposed in this paper. Firstly, the speech Discrete Cosine Transform (DCT) coefficients are modeled by a multivariate Laplace distribution, so the correlations between speech spectral components can be exploited. And then a Minimum-Mean-Square-Error (MMSE) estimator based on the proposed model is derived using a Gaussian scale mixture representation of random vectors. Furthermore, the speech presence uncertainty with the new model is derived to modify the MMSE estimator. Experimental results show that the developed method has better noise suppression performance and lower speech distortion compared to the traditional speech enhancement method. )

实现地震勘探中，地震数据处理的matlab程序。(Implementation of seismic exploration, seismic data processing matlab procedures.)

说明：  matlab实现遗传算法，代码超多，共参考。(realize matlab genetic algorithm, super-multi-code, a total of reference.)

retangular waveguide

this ebook is consist of cloud computing basics

与理论分析结果相比，数据模型归一化，模态振动，包括随机梯度算法，相对梯度算法，基于SVPWM的三电平逆变的matlab仿真，车牌识别定位程序的部分功能，ICA（主分量分析）算法和程序。 ( Compared with the results of theoretical analysis, Normalized data model, modal vibration, Including stochastic gradient algorithm, the relative gradient algorithm, Based on SVPWM three-level inverter matlab simulation, Part of the license plate recognition locator feature, ICA (Principal Component Analysis) algorithm and procedures. )

%solve u_xx + u_yy = f(x,y) % over the region D = [x0,xf,y0,yf] = {(x,y) |x0 <= x <= xf, y0 <= y <= yf} % with the boundary Conditions: % u(x0,y) = bx0(y), u(xf,y) = bxf(y) % u(x,y0) = by0(x), u(x,yf) = byf(x) % Mx = # of subintervals along x axis % My = # of subintervals along y axis % tol : error tolerance % MaxIter: the maximum # of iterations