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carrier
ML estimation of time and frequency offset in OFDM systems
- 2009-03-02 20:21:12下载
- 积分：1
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power_machines
线性变压器在配电网站中的应用仿真，Matlba/Simulink(Linear transformer in distribution simulation web application, Matlba/Simulink)
- 2009-03-17 20:53:11下载
- 积分：1
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BP
说明： BP算法的matlab实现，能较好的得到结果，误差范围较小(BP algorithm matlab implementation, can get better results, less error range)
- 2011-05-04 20:05:49下载
- 积分：1
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Practical-signal-theory
Practical signal theory
- 2013-07-24 22:07:41下载
- 积分：1
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MUSIC-ESPRIT
music算法，
eprsit算法，
matlab仿真(music algorithm, eprsit algorithm, matlab simulation)
- 2013-05-11 10:09:15下载
- 积分：1
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U16-_Lec3
This is my power electronic lecture note on diode rectification.
- 2014-01-18 07:50:40下载
- 积分：1
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chaos1
说明： 混沌时间序列预测法的实现仿真，时间延迟，关联维，最大Lyapauon指数(Chaotic time series prediction method to achieve simulation, time delay, correlation dimension, largest Lyapauon index)
- 2010-05-01 21:08:14下载
- 积分：1
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fsafgcommand_window_text
这个m-文件允许你导出所有在命令窗口中的文本到字符串单元阵列，每个条目是一个从窗口文本行。未分析的原始字符串也可以，如果需要的话。
操作非常简单 -此文件查找在根窗口，并得到适当的Java对象从文本。
我一直在寻找一种方式做，特别是一些软件中的错误我始终跟踪这，似乎已经没有人写了这种方法，所以我现在在这里供您使用。(This m-file allows you to export all text in the Command Window to a cell array of strings, each entry being a line of text from the window. The unparsed raw string is also available, if desired.
Operation is very simple- this file looks for the appropriate java object in the root window and gets text from it.
I was looking for a way to do this, particularly for error tracking in some software I maintain, and nobody seemed to have written up this method, so I present it here for you to use.)
- 2011-05-23 10:33:44下载
- 积分：1
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sim_dukou
渡口模型，系统模拟仿真，排队论，任意输入船道数和模拟次数，输出平均车辆数和各车辆类型数量(Ferry model, system simulation, queuing theory, any input channel number and the number of simulations ship, the output of the average number of vehicles and the number of vehicle types)
- 2013-09-23 21:47:10下载
- 积分：1
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RLS
本程序基于一阶AR模型，u(n)=-0.99u(n-1)+v(n)的线性预测。白噪声v(n)方差0.995.FIR滤波器的抽头数为2.遗忘因子0.98.用RLS算法实现u(n)的线性预测。并附有仿真图片。。(This procedure is based on a first-order AR model, u (n) =-0.99u (n-1)+v (n) of the linear prediction. White noise v (n) the number of taps of the the variance 0.995.FIR filter 2. Forgetting factor 0.98. U (n) of the linear prediction using the RLS algorithm. With simulation Pictures. .)
- 2012-09-20 09:39:59下载
- 积分：1
