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MATLAB
MATLAB的图像处理功能,功能十分强大,内容也很丰富(MATLAB image processing functions, is very powerful, very rich in content)
- 2010-06-15 10:22:55下载
- 积分:1
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rossler
Simulation of Rossler ODE
- 2014-09-14 11:06:22下载
- 积分:1
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LMS
LMS三角定位迭代加权算法 LMS三角定位迭代加权算法 LMS三角定位迭代加权算法(LMS triangulation iterative weighting algorithm LMS triangulation iterative weighting algorithm LMS triangulation iterative weighting algorithm)
- 2013-12-03 09:05:26下载
- 积分:1
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windmatlab
运用wind matlab 进行量化投资, 例子包括 期货 期权 股票 债券等 (some samples for quantitative investing using matlab)
- 2014-08-27 23:59:50下载
- 积分:1
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zoomfft
频谱细化分析的程序,程序包括着逐渐完成的几个过程程序,注意频谱细化是针对开始对象时连续的。(Detailed analysis of the spectrum, the program includes a process of gradual completion of several procedures, attention to refine the spectrum when the object is for consecutive starts.)
- 2013-09-20 17:29:44下载
- 积分:1
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IEEE_9bus
ieee 9-bus system test network implemented in simulink matlab
- 2016-09-12 18:06:56下载
- 积分:1
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graphicMatlab
图像索材,学习图像处理必须的一些常用图片,愿大家能轻轻松松学习图像!(Image cord material, learn to be a number of image processing used pictures, would like to learn that we can easily image!)
- 2009-06-02 20:48:55下载
- 积分:1
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dtc3b
Direct torque control of IM
- 2012-07-06 00:20:35下载
- 积分:1
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modulation-classify
在MATLAB中使用决策论的方法进行调制方式识别,可以识别AM,FM,USB,LSB,ASK,PSK,FSK等多种调制方式(In MATLAB using the decision theory approach to modulation recognition, you can identify the AM, FM, USB, LSB, ASK, PSK, FSK modulation and other)
- 2011-11-11 13:22:19下载
- 积分:1
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Minimum-Risk-Bayes-classifier
这是模式识别中最小风险Bayes分类器的设计方案。在参考例程的情况下,自行完善了在一定先验概率的条件下,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。
调用最小风险贝叶斯分类器决策子函数时,根据先验概率,再根据自行给出的5*5的决策表,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,放入决策数组中。
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”,调用最小风险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,就可以得到在一定先验概率条件下,决策表中不同决策的错误率的统计。
(This is a pattern recognition classifier minimum risk Bayes design .In reference to the case of routine , self- improvement in a certain a priori probability 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 The third step is the 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 .
Bayesian classifier )
- 2012-02-02 20:37:04下载
- 积分:1