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hill
采用爬山法求解优化问题,一共4个文件,函数和脚本分开放(Climbing method used optimization problem, a total of four documents, functions and sub-script open)
- 2007-11-16 01:48:13下载
- 积分:1
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bp
说明: 利用bp算法对鸢尾花数据进行分类的matlab实现程序(Bp algorithm using iris data classification procedures to achieve matlab)
- 2009-05-17 02:14:59下载
- 积分:1
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BPexample01
采用Matlab工具箱函数建立神经网络,对一些基本的神经网络参数进行了说明,深入了解参考Matlab帮助文档。
(Using Matlab toolbox functions to establish neural networks, some of the basic neural network parameters are described to understand the reference to Matlab help documentation.)
- 2009-12-17 21:54:53下载
- 积分:1
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01
说明: 基于MATLAB的语音信号处理之滤波器设计(MATLAB-based speech signal processing of the filter design)
- 2010-01-16 14:46:27下载
- 积分:1
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DopplerCom
相位编码脉冲压缩雷达的多普勒补偿算法(详细),matlab开发仿真
(Phase-coded pulse compression radar Doppler compensation algorithm (detail), matlab development simulation)
- 2020-12-01 16:19:26下载
- 积分:1
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matlab-SIS
matlab 用于sis模型的研究 一篇论文 希望有用(matlab sis)
- 2011-07-21 10:11:38下载
- 积分:1
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Folyd
自己写的Floyd,没有理解Folyd的同学可以拿去参考一下啦!!!!(Wrote it myself Floyd, do not understand Folyd students can refer to you instead!!!!)
- 2009-02-21 18:58:35下载
- 积分:1
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35738594ERRandomGraph
ERRandomGraph matlab代码构造ER随即网络图(matlab for ERRandomGraph)
- 2010-11-22 16:51:50下载
- 积分:1
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HOFFMAN
霍夫曼coding程序,用此程序可以对任意图像进行霍夫曼编码。(Huffman coding procedures, this procedure can be used for any image Huffman coding.)
- 2020-11-10 15:19:46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