The-linear-neural-network

分数阶傅里叶变换的二维峰值搜索，针对线性调频信号的峰值能进行很好估计(D peak search Fractional Fourier transform for the peak chirp signal can be well estimated)

Binary to decimal conversion and Decimal tobinary conversion.

数学建模清华数模讲义\mcm99cb (Mathematical modeling Qinghua digital-analog handouts mcm99cb)

图像增强方法，采用保持形状的灰度变换方法实现多层对比度增强(The image enhancement method,use gray-scale transformation method holding shape to realize multilayer contrast enhancement.)

这是一个完整的描述软件无线电的MATLAB编程，非常适用用仿真，初学者可以(This a complete description of the MATLAB software radio programming, is very suitable for use simulation, beginners can s)

We develop a tracking controller for the dynamic model of unicycle mobile robot by integrating a kinematic controller and a torque controller based on Fuzzy Logic Theory. Computer simulations are presented confirming the performance of the tracking controller and its application to different navigation problems.

model of a LQR controller for the inverted pendulum in simulink

MATLAB常用函数参考，包含了通用命令、运算符和特殊运算符、编程语言结构、基本矩阵函数和操作、基本数学函数、坐标变换、向量运算等特殊函数等常用函数的说明。(MATLAB function reference，it contains the common commands, operators and special operators, programming languages, basic matrix functions and operators, basic math functions, coordinate transformations, vector operations, and other special functions.)

distributed in matlab mfile

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. )