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linearpoweramplifiercharacteristic
Linear power amplifier characteristic
- 2011-07-29 02:57:30下载
- 积分：1
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vibration2
求弹簧-阻尼系统的固有频率和固有振型，并计算系统的响应。(The natural frequencies and natural modes of the spring damping system are calculated and the response of the system is calculated.)
- 2020-11-26 10:19:32下载
- 积分：1
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MatlabPrinciplesOfCommunicationSystemsSimulation
matlab in digital communication
- 2010-11-11 10:50:37下载
- 积分：1
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Matlab
此为matlab教程，主要是关于simulink的实验教程，是学校的内部资料。(This is a matlab tutorial, mainly on the experimental simulink tutorial, is the school' s internal information.)
- 2011-11-04 22:35:59下载
- 积分：1
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GT
基于博弈论的信道选择与功率控制仿真，在20次迭代后达到纳什均衡(Channel selection and power control simulation based on game theory, after 20 iterations to reach the Nash equilibrium)
- 2020-12-11 10:29:17下载
- 积分：1
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1
说明： 主要用于脉冲绘制轮廓图，和对轮廓绘制的分析程序(Used to draw the contour map)
- 2013-03-14 13:09:52下载
- 积分：1
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5
说明： Optimization Example
- 2011-12-01 21:56:53下载
- 积分：1
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lecture5_Finite-Volume-M-ethod
lecture series of matlab
- 2012-10-10 02:44:41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
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AdaptiveLMSequlalization
there are some codes aboutAdaptive equlalization in the telecommunication
- 2010-07-15 23:14:44下载
- 积分：1
