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buck_close_loop
There are 3 models of Buck converter closed loops with PWM done in simulink and they work properly
- 2011-05-21 01:08:59下载
- 积分：1
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rectwindowfilter
lowpass filter using rectangular window
- 2013-03-05 00:15:03下载
- 积分：1
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frequencyoffsetestimateofdm
Algorithm for Frequency estimation
- 2010-06-08 14:31:57下载
- 积分：1
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lorenz
说明： 洛伦兹混沌多涡卷吸引子源代码，复杂程序，用于毕业设计(Multi-scroll chaotic Lorenz attractor source code, complex procedures for graduation)
- 2011-03-24 16:27:46下载
- 积分：1
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MATLAB_application_DSP
说明： 《MATLAB在数字信号处理中的应用》
介绍matlab6.1在数字信号处理领域的基本原理和应用(err)
- 2008-11-23 20:27:34下载
- 积分：1
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cer
通过小程序的仿真是现阶段的定位以及相关内容的撰写(Sure to upload high quality source code and website writing seriously upload information, including content description (at least 20). Try not to let the owners have spent time on the revised instructions you. Unpack the archive and can not have a password)
- 2013-03-21 20:16:31下载
- 积分：1
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mean_shift_tracking
mean shift tracking, 经我修改 可以运行(mean shift tracking code, running successfully.)
- 2010-11-18 10:44:40下载
- 积分：1
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TDD_mode
3gpp release5中对TDD模式的详细描述(3gpp release5 TDD mode to a detailed description of)
- 2007-04-04 21:05:04下载
- 积分：1
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2DFlow_FDM
Program simulating the 2D flow of a Newtonian fluid between two parallel plates using finite diference method.
- 2014-11-26 10:12:35下载
- 积分：1
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Minimum-Bayes-classifier-error-rate
这是模式识别中最小错误率Bayes分类器设计方案。
自行完善了在不同先验概率的条件下，男、女错误率和总错误率的统计，放入各个数组当中。
全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。
调用最大似然估计求取概率密度子函数时，第一步获取样本数据，存储为矩阵；第二步对矩阵的每一行求和，并除以样本总数N，得到平均值向量；第三步是应用公式（3-43）采用矩阵运算和循环控制语句，求得协方差矩阵；第四步通过协方差矩阵求得方差和相关系数，从而得到概率密度函数。
调用最小错误率贝叶斯分类器决策子函数时，根据先验概率数组，通过比较概率大小判断一个体重身高二维向量代表的人是男是女。
主函数第一步打开“MAIL.TXT”和“FEMALE.TXT”文件，并调用最大似然估计求取概率密度子函数，对分类器进行训练。第二步打开“test2.txt”，调用最小错误率贝叶斯分类器决策子函数，然后再将数组中逐一与已知性别的数据比较，就可以得到不同先验概率条件下错误率的统计。
(This is the minimum error rate pattern recognition Bayes classifier design.
Self- improvement prior probability in different conditions , male , female and total error rate error rate statistics , into which each array .
All programs from the main function , maximum likelihood estimation subroutine strike probability density , the minimum error rate Bayesian classifier composed of decision-making three subfunctions .
Strike called maximum likelihood estimate probability density subroutine , the first step to obtain the sample data , stored as a matrix the second step of the matrix, each row sum , and divided by the total number of samples N, be the average vector third step is to application of the formula ( 3-43 ) using matrix and loop control statements , obtain the covariance matrix fourth step through the variance-covariance matrix and correlation coefficient obtained , resulting in the probability density function .
Call the minimum error rate decision Functions Bayesian)
- 2012-02-02 20:33:06下载
- 积分：1
