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LDPC
LDPC码的MATLAB仿真程序,希望对大家有用！()
- 2008-02-19 09:50:07下载
- 积分：1
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xindiantu
利用matlab模拟出心电图，并对心电图做相应处理！(Using matlab simulated ECG, electrocardiogram and accordingly deal with!)
- 2009-11-19 21:17:06下载
- 积分：1
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qpsk
说明： matlab中用simulink模块实现qpsk调制，包括模块及其主函数
(matlab with simulink module QPSK modulation, including the module and its main function)
- 2008-09-10 16:01:22下载
- 积分：1
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optimal
优化问题实验
优化问题实验
优化问题实验(optiaml funtion)
- 2009-02-04 22:15:20下载
- 积分：1
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RungeKutta_4
说明： 以lorenz吸引子为例说明四阶定步长Runge-Kutta算法 详情见程序说明(to attract son as an example to illustrate four bands will step Runge- Kutta algorithm detailed description of the procedures)
- 2006-04-10 12:20:56下载
- 积分：1
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MATLABsoftwarefoundation
说明： MATLAB软件基础，详细介绍了matlab软件的基础操作。(MATLAB software foundation, described in detail the basis for operation of matlab software.)
- 2010-04-28 18:34:57下载
- 积分：1
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simulink
simulink.zip,MATLAB/SIMULINK通信系统建模与仿真实例分析(著译者,邵玉斌)教材里的例题源程序和模块，以及课后题源程序和模块(simulink.zip MATLAB/SIMULINK communications system modeling and simulation examples analysis of the source code and modules of the examples in the textbook, as well as after-school title source code and modules)
- 2013-01-04 10:43:37下载
- 积分：1
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shanon
shannon channel codeing project
- 2015-01-17 11:20:17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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面向MATLAB工具箱的神经网络理论与应用_10206284
可以降维分析，还有bp神经网络，非常方便学习。大家可以随意下载，(Dimensionality reduction analysis)
- 2020-06-24 08:40:01下载
- 积分：1
