sunspotstx

说明：  一种基于信息熵的Matlab端点检测算法，抗噪性能比较好(Matlab based on information entropy of the endpoint detection algorithm, better anti-noise performance)

采用并网电压有效值控制，作为电流内环的给定参考值，单位功率因素运行(use RMS control the voltage and the current)

说明：  灰度共生矩阵提取纹理特征，极快的MATLAB代码(GLCM texture feature extractionfast MATLAB code)

说明：  This paper presents a Matlab Simulink model of a single-phase 2kVA Voltage Controlled Voltage Source

Cross entropy for TSP problem matlab file

故障诊断方面的一篇文章，发表在Automatica上，具有很大的参考意义。(Fault diagnosis of an article published in Automatica, and has great reference value.)

vc++和matlab的图像处理应用程序，可以相互调用，属于混合编程的各个实例程序。(VC++ and MATLAB image processing applications, can call each other, belonging to the mixed programming various examples of procedures.)

simulation modulate & demod PM

本程序是移动协作定位算法的仿真程序，各种条件下的代码都有，可以直接运行。(This progrem is a mobile cooperative localization algorithm, various conditions have the code, can be directly run.)

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. )