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自己收集到的指纹预处理的各种方法，推荐给需要的朋友们。(Their fingerprints collected from the various methods of pretreatment, required to recommend friends.)

VC++实现vc调用matlab的程序的简单例子。vc6.0环境下测试通过。(VC vc call Matlab procedures simple example. Vc6.0 environment test.)

this program estimated the pitch contour of a given speech signal.

利用马斯京根原理，根据水文气象等历史数据进行下一时段的预测。(According to Muskingum principle,the forecast of the next time can be drawn by the historical hydro-meteorological data.)

鉴于LCD方法存在的问题，本文提出了一种基于互相关匹配端点延拓局部特征尺度分解（Cross-correlation matching endpoint Extension Local Characteristic scale Decomposition，简称CELCD），由于LCD分解原理是依据信号的局部极值点信息不断进行筛分信号，在信号分解时需要先确定信号的局部极值点，而信号的两个端点可能不是极值点，因此在信号两端点就会出现虚假成分，且该现象随着分解的进行向数据内部扩散，产生端点效应，导致分解结果失真。而CELCD方法的本质在于探索待分解信号前后端的数据规律，延长波形，使得端点效应不出现在原始信号分解的片段上，从而消除端点效应。(Given the LCD method has a problem, this paper presents a cross-correlation based on local feature matching endpoint extension scale decomposition (Cross-correlation matching endpoint Extension Local Characteristic scale Decomposition, referred CELCD), since the LCD decomposition principle is based on the signal of local optima ongoing screening point information signal, when the signal decomposition needed to determine local extreme point of the signal, and the two endpoints signals may not be extreme point, so the two end points of the signal will be fraudulent, and that the phenomenon with decomposition of the data in the internal diffusion, resulting end effect, leading to decomposition distortion. The essence of the method is to explore CELCD data signal to be decomposed before and after the end of the law, to extend the waveform, so the end effect does not appear on the original signal decomposition fragments now to eliminate the end effect.)

使用卡尔曼滤波器对物体的未来状态进行预测和估计。(Using the kalman filter to predict the station of the object.)

Brushless DC Motor Control Made Easy

Algorithm to find Depth of Image

这是MAtlab与DSP应用中的第2掌的例子程序(This is the Matlab and DSP applications, the first 2 examples of palm procedures)

This code was used for making the practical measurements in section 2.3 of my thesis. This Matlab code allows an OFDM signal to be generated based on an input data file. The data can be random data, a grey scale image, a wave file, or any type of file. The generated OFDM signal is stored as a windows wave file, allowing it to be viewed, listened to and manipulated in other programs. The modified wave file can then be decoded by the receiver software to extract the original data. This code was developed for the experiments that I performed in my honours thesis, and thus has not been fully debugged. This is the original code developed for the thesis and so has several problems with it. The BER performance given by the simulations is infact Symbol Error Rate. (This code was used for making the practical measurements in section 2.3 of my thesis. This M atlab code allows an OFDM signal to be generated based on an input data file. The data can be rando m data, a gray scale image, a wave file, or any type of file. The OFDM signal is generated stored as a windows wave file, allowing it to be viewed. listened to and manipulated in other programs. The modified wave file can then be decoded by the receiver software to extract the original data . This code was developed for the experiments th at I performed in my honors thesis, and thus has not been fully debugged. This is the original code developed for the thesis and so ha 's several problems with it. The BER performance given by the simulations is infact Symbol Error Rate.)