Produce-small

用matlab识现人脸表情识别的方法，对于初学者matlab以及研究人脸表情识别有很大的帮助(Matlab knowledge with Facial Expression Recognition is the way to matlab for beginners as well as facial expression recognition is very useful to)

signal processing using matlab (example)

使用重构向空间捕捉非线性特征。来源于国外网站，请注明出处。(RPS Toolbox - This toolbox contains Matlab functions to capture the nonlinearities of the speech production system using reconstructed phase space (RPS) techniques.)

Simulation doppler effect in matlab

particle filter based on color to track object movement

BDS检验的matlab实现，检验样本是否为独立同分布的数据(BDS test matlab implementation, testing whether the sample is independent and identically distributed data)

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. )

knn用于分类的matlab源码，短小精悍(knn matlab source code for the classification, dapper)

matlab编写的元胞自动机，滤波求和方式实现宽带波束形成，最大似然（ML）准则和最大后验概率（MAP）准则，各种资源分配算法实现，包括最小二乘法、SVM、神经网络、1_k近邻法,关于小波的matlab复合分析，多姿态，多角度，有不同光照,保证准确无误，是学习通信的好帮手。( matlab prepared cellular automata, Filtering summation way broadband beamforming, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Various resource allocation algorithm, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Matlab wavelet analysis on complex, Much posture, multi-angle, have different light, Ensure accurate communication is learning a good helper.)

this will helpful for region merging algorithm