Extracting-Embedded-Images-From-An-Assembly---Cod

提供MATLAB的算法源程序100个，有效节省了MATLAB初学着的掌握程度。(MATLAB algorithms to provide the source code 100, effective savings of MATLAB beginner s grasp of the extent.)

绘图，其中包含绘图的基本Matlab的源程序，是M文件，还有PPT的相关解释(Drawing, which contains the basic drawing of Matlab source code, is M-file, as well as the relevant explanation PPT)

用matlab求图像阈值分析程序，一种是直方图阈值法一种是最大类间方差(Using matlab and image threshold analysis program, a variance between a Histogram method is the largest class)

this code is mainly for frequency sampling. It has the carrier and the sampling frequency.

线性调频信号脉冲压缩仿真程序，输出目标一维距离像(a simulation of LFM pulse compression , A high resolution range profile will be obtained)

牛顿欧拉递推算法——机器人动力学算法，使用matlab语言描述逆向动力学算法。(Newton-Euler recursive algorithm- Robot dynamics algorithms, the use of language to describe the reverse dynamics matlab algorithm.)

独立成分分析（Independent Component Analysis, ICA）是近年来发展起来的一种有效的盲分离技术，最早是由法国学者Herault和Jutten于1986年提出。ICA方法的提出最初是用来解决“鸡尾酒会”问题，其过程可以归纳为，在源信号与传输通道参数均未知的情况下，仅根据源信号的统计特性，出现测信号恢复出源信号。ICA分析的关键在于根据一定的优化准则建立描述输出信号独立程度的优化判据，即目标函数，并设计相应的优化算法，寻求最优的分离矩阵，使得输出信号中各分量尽可能相互独立。采用ICA方法对信号进行盲分离时，可避免过多地受大能量噪声成分的影响，将部分小能量信号源识别出来。随着ICA技术的不断发展，目前ICA技术已经广泛应用于语音增强、音频识别、通信、医学信号处理、金融数据挖掘、图像消噪、数字水印、遥感等领域，并取得了一定的研究成果。(Independent Component Analysis (ICA) Component ini order, developed in recent years is a kind of effective separation technology, originally from French scholars Herault and Jutten in 1986. The proposed method is initially ICA to solve the "cocktail" problem, the process can be divided into, in the source signal transmission channels and in the case of unknown parameters according to the source of the signals, and the statistical characteristics of recovering the source signal. According to the analysis of the ICA key lies in the establishment of optimal criteria described the output signal of the independent, objective function optimization criterion, and the corresponding optimization algorithm, the optimum )

matlab联合vc++仿真，最近刚学的，用的上，不错不错。(Joint vc++ matlab simulation, recently learned, the use, good good.)

xiao che mo ni, Matlab+Simulink(car control model)

说明：  sift特征提取，然后再利用svm算法实现特征分类预测(SIFT feature extraction, and then use SVM algorithm to achieve feature classification and prediction)