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Using Matlab to solve some engineering problems

DHMM问题3matlab实现，即给出训练数据，求解（A，B,pi）(Implement of DHMM，i.e，given training data ,estimate (P,Q,pi))

主要用于基于matlab的图像处理，如图像增强、边缘检测、图像变换等(Mainly used for based on the matlab image processing, such as image enhancement, edge detection, and the image transformation, etc)

一个陷波滤波器实例,含有采集到的数据文档(Examples of a notch filter, a document containing the data collected)

使用pca和svm的方法对人脸进行识别和检测，最终达到人脸识别的功能(Face recognition and detection using PCA and SVM methods, and finally achieve the function of face recognition)

matlab偏微分方程的解法全解，好实用，如果你对matlab甚至稍微了解一点的话，你都不容错过的下载文档(the matlab Partial Differential Equations and full solution practical If you matlab even slightly understand a little, you have to download the document not to be missed)

说明：  有关多用户预编码下的信道容量，预编码方案包括：ChannelInversion和RegularizedChannelInversion

GloptiPoly 3: moments, optimization and semidefinite programming. Gloptipoly 3 is intended to solve, or at least approximate, the Generalized Problem of Moments (GPM), an infinite-dimensional optimization problem which can be viewed as an extension of the classical problem of moments [8]. From a theoretical viewpoint, the GPM has developments and impact in various areas of mathematics such as algebra, Fourier analysis, functional analysis, operator theory, probability and statistics, to cite a few. In addition, and despite a rather simple and short formulation, the GPM has a large number of important applications in various fields such as optimization, probability, finance, control, signal processing, chemistry, cristallography, tomography, etc. For an account of various methodologies as well as some of potential applications, the interested reader is referred to [1, 2] and the nice collection of papers [5].(GloptiPoly 3: moments, optimization andsemidefinite programming.Gloptipoly 3 is intended to solve, or at least approximate, the Generalized Problem ofMoments (GPM), an infinite-dimensional optimization problem which can be viewed asan extension of the classical problem of moments [8] . From a theoretical viewpoint, theGPM has developments and impact in various areas of mathematics such as algebra, Fourier analysis, functional analysis, operator theory, probability and statistics, to citea few. In addition, and despite a rather simple and short formulation, the GPM has alarge number of important applications in various fields such as optimization, probability, finance, control, signal processing, chemistry, cristallography, tomography, etc. For anaccount of various methodologies as well as some of potential applications, the interestedreader is referred to [ 1, 2] and the nice collection of papers [5].)

control simulation examples

实现了车辆目标的背景建模、前景检测、阴影消除、车辆跟踪。(The vehicle to achieve the target of the background modeling, foreground detection, shadow elimination, vehicle tracking.)