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说明：  MATLAB进行有限元分析时应用该用限元工具箱，很好用的(MATLAB finite element analysis application of the Limited yuan toolbox, with the good)

在坐标轴2上，针对二值图像进行分水岭算法的分割以及最大熵阈值算法的分割，并将分割出的部分显示在坐标轴3上。(Axis for the binary image segmentation of the watershed algorithm and maximum entropy threshold algorithm split, and the split part is displayed in the axis 3.)

MATLAB Programs that can be used by beginners to learn the basics. College of Engineering, Cherthala.

returns the number of boundary segments for the P08 region

一种未知信源数的高分辨DOA 估计算法：众多性能优良的超分辨波达方向(DOA)估计算法通常需要预先判定信源数目，然而，现有的信源数估计 算法在有限采样快拍条件下，估计性能随着信噪比的降低而下降，错误概率也相应增加，最终导致DOA 估计失败。 该文提出一种超分辨的DOA 估计算法，此算法不需要预判信源个数和进行特征值分解，同时在时变环境中，针对 快拍数较少的情况下，依然保持较高的角度分辨能力，可以被认为是综合了Capon 法和MUSIC 法的优点。(Algorithm on High Resolution DOA Estimation without Sources Number：Many of the super resolution DOA(Direction-Of-Arrival) estimation algorithms presume the number of signal sources. Since the sample snapshot is limited, however, the available algorithms on source number estimation may fail at lower SNR. In this paper, a novel algorithm for high resolution DOA estimation is proposed, which not only skips sources number estimation and EVD, but also behaves satisfactorily with a few snapshot, it may be viewed as a combination of merit of conventional Capon and MUSIC method.)

将输入d进行扩张，方法是在d的每个数据中插入M-1个零值。 如输入d=[1,2,3,4] M=3 输出out=[1 0 0 2 0 0 3 0 0 4 0 0](To expand the input d, the method is to insert each data d, M-1 zero value. If the input d = [1,2,3,4] M = 3 output out = [1 0 0 2 0 0 3 0 0 4 0 0])

AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.(AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.)

是一些常用的时域特征提取方法，再次进行整合，方便大家的提取(Are some commonly used time domain feature extraction method, integrate again, facilitate everybody extraction )

Used to make fast Source Code for Andriod.

动态矩阵控制DMC的一个很好的matlab程序,可以应用到很多的领域(a program of dynamic matrix conrol using matlab)