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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. )

蚁群算法，对无人机路径进行有效规划，避免无人机相撞事故(Colony algorithm, effective UAV path planning to avoid drone crash)

说明：  可计算序列的信息熵、两个序列间的联合信息熵和互信息(This file can calculate the entropy, joint entropy and mutual information)

此代码为主元分析法的应用代码，欢迎有需要的人士取用。(Principal component analysis of the application code, please access.)

绘制系统带有Gershgorin带的逆Nyquist图(gershgorin mapping system with the inverse Nyquist zone map)

imnverted pendulum bymyself it is used for simulation about robot

%% 用聚类法确定葡萄酒分级 % 《MATLAB数学建模方法与实践》(《MATLAB在数学建模中的应用》升级版)，北航出版社，卓金武、王鸿钧编著.(Classification of wine by clustering method Mathematical Modeling Methods and Practice in MATLAB (Upgraded Edition of Application of MATLAB in Mathematical Modeling), edited by Zhuo Jinwu and Wang Hongjun, Beihang Publishing House.)

cdma信号的构建，对误码率的分析比较突出。(Construction of cdma signals, bit error rate analysis of the more prominent.)

penalty function_fletcheReeves

This getting started exercise will guide you through the step-by-step process of transforming a MATLAB floating-point model into a hardware module that can be implemented in silicon (FPGA or ASIC). The design is a general purpose FIR filter taken from the AccelDSP Examples directory.(This exercise will guide y ou through the step-by-step process of transfo rming a MATLAB floating-point model into a hard ware module that can be implemented in silicon ( FPGA or ASIC). The design is a general purpose FI R filter taken from the AccelDSP Examples direc tory.)