svm

MPC using steady state model

matlab读取1979-2009年尼诺3指数并画出随年份变化的曲线的程序(Matlab read 1979-2009 nino 3 index and draw the curve of the change of the year with the program )

基于MATLAB的simulink汽车仿真模型，按功能结构分割，得到汽车的能源-动力学模型(MATLAB simulation model based on the simulink car, according to the functional structure segmentation, automotive energy- kinetic model)

MATLAB 教程，适用于初学者，也可用于自学，介绍了MATLAB基本的编程技巧。(MATLAB tutorial for beginners, and can also be used for self-study, MATLAB basic programming skills.)

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. )

a complete biblio to control the asynchronous machine

包含了一个合成孔径雷达点目标回波模拟和R-D算法和一个距离参考函数(SAR RD imaging algorithm)

histogram of each part from RGB image

用matlab处理音频, 对一段音频加入噪声然后滤除噪声还原, 绘制过程中的频谱图(Matlab deal with audio, for adding some audio noise reduction and filter noise, rendering the process of spectrum)

matlab矩阵操作大全，还包括一些特殊矩阵的生成(matlab matrix operations Daquan, including the formation of some special matrices)