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thisisaanother erettt exaple

自己建立的iclark变换模块，根据TI公司永磁电动机例程编写(iclark tansform created by myself, based on TI s permanent magnet motor routines)

基于小波变换的正交匹配追踪算法及其应用先介绍了压缩感知的基本原理以及理论模型，然后详细阐述了匹配追踪(Ⅷ)以及正交匹配追踪(()脚) 两种重构算法，进而提出了基于小波变换的正交匹配追踪算法(wOⅧ)，即先将信号经过单层小波变换，保留信号的 低频部分，只对高频稀疏部分进行压缩，然后利用正交匹配追踪算法进行重构，最后对低频及处理后得到的高频部分 进行小波反变换得到重构信号。(Based on orthogonal wavelet transform matching tracking algorithm and its application to the basic principles and theoretical models compressed sensing, and then elaborated matching pursuit (Ⅷ) and orthogonal matching pursuit )

how to calculate the impulse response from the frequency response of a Power delay profile

matlab work of matrix converter.......................

说明：  ：Mean—shift算法是一种非参数密度估计算法，可以实现快速的最优匹配，在目标的实时跟踪领域起着非常 重要的作用。为了有效的将Mean—shift算法应用到灰度图像中，采用了以方向直方图建立目标模型的策略，提出了在灰 度图像中以Mean—shift为核心的目标跟踪算法。实验结果表明，该算法具有不受光照条件影响的优点，在低对比度的情 况下仍能实现稳定、实时的跟踪目标。(: Mean-shift algorithm is a nonparametric density estimation algorithm, the optimal matching can be fast, real-time tracking fields in the target plays an important role. In order to effectively Mean-shift algorithm will be applied to the gray image, the histogram used to establish the direction of the strategy target model is proposed in the gray image to Mean-shift tracking algorithm as the core. Experimental results show that the algorithm has the advantage of not lighting conditions, in the case of low contrast can still achieve stability, real-time tracking of targets.)

The basic snake segmentation (2d and 3d). A snake is an active (moving) contour, in which the points are attracted by edges and other boundaries. To keep the contour smooth, an membrame and thin plate energy is used as regularization.

this code is implementaion for A Level Set Method for Image Segmentation in the Presence of intensity Inhomogeneities With Application to MRI. I used this code and it has a trus answer

matlab源码，实现利用霍夫变换的直线检测(matlab source code, line detection using Hough Transform)

这个程序的功能是：当知道自变量的范围时，实现求函数的极大值(Function of this program is: when you know the scope of the argument when seeking to achieve maximum value function)