watermark

程序包涵盖了超宽带书中的函数，并进行了主程序的编写，最后构成了TH-PPM系统仿真基本程序(Package covers a function of the book Ultra-Wideband, and the preparation of the main program, the final composition of the TH-PPM system, the basic procedures for simulation)

将两个矩阵的卷积运算转换为构造的新矩阵的相乘运算(The two matrix of convolution operation into the matrix multiplication)

Application Notes for EM4095

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三维绘制图，可以实现三维曲面图的旋转动画；用于文献汇报等。(MATLAB three-dimensional sketch, animation can rotate a three-dimensional surface plot for reports and other literature.)

门式刚架辅助设计工具箱 ，计算工具箱好用(rigid frame)

This MATLAB Code will help to determine the watermark and its extraction properties like PSNR

用来求光纤的材料色散，并画出其材料色散曲线。(material dispersion)

Input: X, training data, dim*num Y, training data labels, num*class para.alpha, para.beta, regularization parameters para.rd, reduced dimensionality Web Image Annotation via Subspace-Sparsity Collaborated Feature Selection. Zhigang Ma, Feiping Nie, Yi Yang, Jasper Uijlings, and Nicu Sebe. IEEE Transactions on Multimedia (TMM) 14(4):1021-1030, 2012.

我自己写的小波神经网络的Matlab程序，包含了单维的高维的两种网络模型，比较全面，而且代码中加入开发的初始化算法，使用时只需要更换训练样本就可以了。希望对论文写作有所帮助(I wrote it myself WNN Matlab procedures, includes a one-dimensional two high-dimensional network model, a more comprehensive, but also to add code to initialize the development of algorithms, using only training samples need to replace it. Writing wish to be helpful)