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ICA极大似然估计的自然梯度法仿真实例，并计算了串音误差( An experiment of ICA by MLE,including psnr)

由于系统因素之间关系非常复杂，特别是其表面现象及变化的随机性、模糊性和灰色性，使人们在观察、分析、预测和决策时得不到足够的信息，找不到主要矛盾，从而给复杂系统的系统分析带来困难。这就需要灰色关联分析。(Because the system is very complex relationship between factors, especially changes in the surface phenomena and random, fuzzy and gray so that people in the observation, analysis, forecasting and decision-making can not get enough information, can not find the main contradictions thus to the complex system of systems analysis difficult. This requires gray relational analysis.)

说明：  实现FSK调制的详细过程，对学习很有帮助，必须顶(Detailed process to achieve FSK modulation, useful for learning to be top)

用matlab写的经验模式分解程序。可作希尔伯特-黄变换，画时频图。(Empirical mode decomposition process Written by matlab .It Can be used for Hilbert- Huang Transform and time-frequency analysis.)

基于Matlab编程的指纹识别代码中的细化部分代码(Matlab-based fingerprint identification code programmed in the refinement part of the code)

matlab simulation in tl and cable

对给定的信息序列进行Hamming编码，给出码字——C++汉明编码(Hamming coding sequence of the given information, code word- c++ Hamming coding are presented)

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. )

matlab rgb to lab code color space

this codes present SVM