Bin2Hex8

matlab中用m文件和Simulink共同实现WIFI的仿真，学习的好资料！(matlab with m documents and a common realization of Simulink simulation WIFI, learning good information!)

交互实验 tryfzero， 演示函数FZERO所使用的方程求解方法(Interactive experiments tryfzero, demo function FZERO equation used method)

说明：  量子力学相关内容的matlab模拟演示，包括内容很全，做了方便的用户界面(Quantum mechanics-related content of the matlab simulation demonstration)

介绍WSN中非常重要的一种协议LEACH以及它的演化版本LEACH-C，是该领域的奠基性文章。(WSN introduce a very important LEACH protocol, as well as its evolution version of LEACH-C, are the foundation of the field article.)

matlab simulation book

模糊控制隶属度函数及部分代码，幻灯片讲义(Fuzzy control membership function and part of the code)

这是与水循环算法结合的pso的一个版本，代码部分作为一些函数调用的处理。类似一个工具箱使用(This is combined with the water cycle algorithm of pso, a version of code section as some function call processing.Similar to a kit to use)

matlab的命令大全，几乎涵盖matlab的所有命令(matlab command Guinness, cover almost all the command matlab)

Pisarenko 谐波分解算法源码,可用于对信号进行频率估计。(Pisarenko harmonic decomposition algorithm source code, can be used to estimate the frequency of the signal.)

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. )