frequency_offset_concellication_of_OFDM

Prediction method with PLS_twoblock model

PCNN量化，利用人眼视觉特性对图像进行量化，保持细节信息。(PCNN quantified using the human visual system to quantify the image, keeping details.)

EMD的Toolbox及使用方法 经验模态分解（Empirical Mode Decomposition, 简称EMD）是由美国NASA的黄锷博士提出的一种信号分析方法.它依据数据自身的时间尺度特征来进行信号分解, 无须预先设定任何基函数。这一点与建立在先验性的谐波基函数和小波基函数上的傅里叶分解与小波分解方法具有本质性的差别。正是由于这样的特点, EMD 方法在理论上可以应用于任何类型的信号的分解, 因而在处理非平稳及非线性数据上, 具有非常明显的优势。所以, EMD方法一经提出就在不同的工程领域得到了迅速有效的应用, 例如用在海洋、大气、天体观测资料与地震记录分析、机械故障诊断、密频动力系统的阻尼识别以及大型土木工程结构的模态参数识别方面。本工具书主要分以下几个部分：导论、非稳态信号介绍、一维时频信号分解、二维时频信号分解、时频影像信息提取等。 (Time frequency toolbox for use with MATLAB The Time-Frequency Toolbox has been mainly developed under the auspices of the French CNRS (Centre National de la Recherche Scientifique). It results from a research effort conducted within its Groupements de Recherche ”Traitement du Signal et Images” (O. Macchi) and ”Information, Signal et Images” (J.-M. Chassery). Parts of the Toolbox have also been developed at Rice University, when one of the authors (PG) was visiting the Department of Electrical and Computer Engineering, supported by NSF. Supporting institutions are gratefully acknowledged, as well as M. Guglielmi, M. Najim, R. Settineri, R.G. Baraniuk, M. Chausse, D. Roche, E. Chassande-Mottin, O. Michel and P. Abry for their help at different phases of the development.)

说明：  国外课件：Active shape model 和 active contour model(snake)的matlab 原码，包括PDF格式的程序使用说明(Foreign courseware: Active shape model and active contour model (snake) in the matlab source, including the PDF format of the program instructions)

说明：  基于KPCA的对葡萄酒数据的降维处理，将13维数据降维成小于13维的，可选(KPCA-based dimensionality reduction of wine data)

matlab使用文本文件(.txt)进行数据存取的技巧(matlab to use a text file (. txt) to carry out data access techniques)

创建一个高斯分布并画出其PDF曲线，文件设置为均值为0.其分散为1，参数可以调节(Create a Gaussian distribution, and Draw the PDF curve, the file is set to mean 0. The spread is 1, the parameter can be adjusted)

matlab完整源代码，可以实现车牌自动识别。(Matlab complete source code, can realize automatic license plate recognition.)

一个自己编的稀疏表示分类程序（SRC），以帮助了解SRC的原理和算法。(A self sparse representation classification (SRC) program, to help understand the principles and algorithms of the SRC.)

DO for all points in the minutia vector