classicalSegment1

数据记录的是在意大利某一地区同一区域上三种不同品种的酒的化学成分分析，这里利用svm进行分类(Data records is a region in Italy on the same area of three different varieties of wine chemical analysis, where the use of svm classification)

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. )

this file is an ac to ac controller. you can control the output by adjusting the firing angle of the SCR.

说明：  方程组追赶法的C++程序以及MATLAB源程序(Equations chase law procedures and the MATLAB C++ source code)

make image RGB to monocrhome

说明：  几篇粗糙集的论文文献，感觉不错，跟大家分享(Papers several rough set literature, I feel good, to share with you)

说明：  QPSK卷积码程序,包含误码率曲线，星座图等程序(QPSK convolutional code procedures)

一个关于MUSIC算法的源程序，有一点问题，哪位高手帮忙看看为什么不能运行，谢谢了！(one on the source MUSIC, 1:00. Which expert help to find out why not running, thank you!)

％threerayRayleigh.m ％ Last Homework pp. 253 5.31 (Second Edition English) ％ Default parameters ％ (threerayRayleigh.m%% Last Homework pp. 2 53 5.31 (English Second Edition) para% Default meters%)

使用SVM中的1V1以及1VO算法实现对数据的分类以及matlab实现(Classification of data and implementation of matlab using 1V1 and 1VO algorithms in SVM)