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QPSKwithmatlabcode
详细讲述了∏/4-DQPSK调制和解调原理,并提供了matlab实现的代码(Detail the Π/4-DQPSK modulation and demodulation, and provides a matlab implementation of the code)
- 2010-07-25 14:13:52下载
- 积分：1
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Image-morphology
图像形态学变换及其应用matlab源代码(Image morphological transformation and its applications matlab source code)
- 2014-11-01 11:26:23下载
- 积分：1
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Untitled
打靶法的matlab实现，需要输入的变量较多，程序不是十分简便(Matlab implementation of the shooting method)
- 2012-12-28 21:18:33下载
- 积分：1
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outline
outline, spanning tree
- 2012-04-09 11:57:15下载
- 积分：1
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zhuchengfenfenxiheyezhifenxi
通过例子，解释主成分分析和因子分析之间的区别，方便大家学习(Examples to explain the difference between the principal component analysis and factor analysis to facilitate learning)
- 2012-05-19 12:14:34下载
- 积分：1
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bfgs4
bfgs optimization method
- 2013-12-01 03:59:20下载
- 积分：1
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pv_bingwang
仿真软件MATLAb搭出来的一个光伏电池并入微电网模型，大家可以参考下(Simulation software MATLAb take out a photovoltaic cell and nuanced grid model, we can refer to)
- 2013-11-03 11:09:25下载
- 积分：1
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benchmark
optimization of benchmark function by different methods
- 2012-11-22 17:36:04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
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FFTorIFFT
用于信号处理的matlab小程序。傅里叶变换和傅里叶逆变换(fft or ifft)
- 2020-11-26 11:49:31下载
- 积分：1
