lyapunov1

本程序是用MATLAB实现的小波零树图像压缩算法，请阅读附件中的README得到用法。注意，目前只是适用128×128的图像。(This procedure is used MATLAB realize the wavelet zerotree image compression algorithm, please read the README in the annex to be usage. Note that currently only applies to 128 × 128 images.)

说明：  这个代码是关于神经网络的matlab代码，我觉得效果不错。(This code is on the neural network matlab code, I think good results.)

朋友发给我的完整的EMD程序，可能对搞这方面研究的人有帮助(A friend sent me the full EMD program, engage in research in this area may help people)

SeDuMi 是一个求解半正定规划的算法包，这是项目最新发布的源代码。(Welcome to SeDuMi 1.3 SeDuMi is a Matlab Toolbox for Linear, Second order, Semidefinite or mixed problems. It can handle free variables and complex data as well. To obtain the latest version of SeDuMi, see http://sedumi.ie.lehigh.edu Installation instructions can be found in the file Install.txt After you installed the binaries please type help sedumi in Matlab to get more information. Example problems can be found in the folder /examples, documentation is in /doc. For a list of changes check the file Changelog.txt.)

主成分分析代码，用matlab实现的，请大家参阅。(Principal component analysis code, matlab implementation, please refer to the.)

图像融合，实现两幅图像的特征融合.该程序使用小波分解的方法先对两幅图像进行小波分解，然后进行多种方法对图像进行特征融合(Fusion, feature fusion of two images to achieve. The method uses wavelet decomposition of the two images before wavelet decomposition, and then features a variety of methods of image fusion)

提供了对象已知与未知的广义预测控制（GPC）算法，包含有单步与多部的Diophanine方程求解。(Provides object known and unknown generalized predictive control (GPC) algorithm, includeing single-step and multi-unit Diophanine equation.)

it is dataset for matlab vowel

说明：  主成分分析法将图像分为低秩部分和稀疏部分(Principal Component Analysis (PCA) divides images into low rank and sparse parts)

线性预测分析是现代语音信号处理中最核心的技术之一，为现代语音信号处理的飞速发展立下了赫赫功劳，在语音分析、合成、编码、识别等方面都有着广泛的应用，至今仍是最有效的语音分析技术之一。(Linear prediction analysis is the most modern speech signal processing one of the core technology for the modern rapid development of voice signal processing and established illustrious contribution of the speech analysis, synthesis, coding, recognition and so on are widely used, still is the most effective voice analysis technologies.)