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BLAST_MTNR
说明： 程序是MIMO-OFDM系统下，对BLAST码的编译码，信道估计及解码算法的仿真程序(Procedure is MIMO-OFDM system, the codec code to BLAST, channel estimation and decoding algorithm of the simulation program)
- 2008-10-10 12:51:30下载
- 积分：1
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pid-matlab
简单pid和串级pid的matlab仿真(Simple cascade pid pid and the matlab simulation)
- 2011-07-26 12:56:03下载
- 积分：1
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LFnewton
power flow analysis using newton raphson method
- 2013-07-27 19:00:20下载
- 积分：1
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Mackey-Glass
Mackey-Glass prediction series
- 2010-02-06 13:02:29下载
- 积分：1
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MATLABnihe.rar
说明： 介绍怎样利用matlab对曲线进行拟合的文章，实用性很高(Introduce how to make use of matlab curve fitting of the article, practical, high)
- 2008-09-04 22:07:37下载
- 积分：1
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MITmatlab
说明： 麻省理工学院的MATLAB基础学习教程资料(Massachusetts Institute of Technology-based learning MATLAB Tutorial Information)
- 2008-10-28 10:34:18下载
- 积分：1
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dynamic-meterology(5_9chapter)part-2
an introduction to dynamic meterology chapter 5-9 chapter matlab所有代码 气象专业经典资料(an introduction to dynamic meterology chapter 5-9 matlab code)
- 2013-12-11 18:42:30下载
- 积分：1
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QPSK
An all-optical regeneration scheme for DQPSK and QPSK signals using phase-sensitive amplifiers (PSAs) is studied and its effectiveness
is investigated through numerical simulations. By leveraging the ability of PSAs to provide phase and amplitude regenerative amplification,
we show significant simultaneous suppression of both phase and amplitude noises of (D)QPSK signals under optimized
conditions. The reduction in the phase noise variance of a noise-corrupted DQPSK signal obtained by one such regenerative amplification
can be as large as 5.5 folds, showing its good potential for distributed optical regeneration of (D)QPSK signals.
2008 Elsevier B.V. All rights reserved.
- 2015-03-23 12:52:39下载
- 积分：1
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蒙特卡洛
说明： 可实现雷达目标检测与跟踪，可绘制所有航迹(Radar target detection and tracking, can draw tracks)
- 2020-10-30 17:00:55下载
- 积分：1
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gm11
function exp85
clear all
p=[0:0.1:1.1]
t=[22.4570 26.6012 12.6416 5.9367 6.9265 28.2432 31.5068 37.0166 7.8947 1.0398 12.7095]
net=newff([0 1],[5 1],{ tansig purelin }, traingdx , learngdm )
net.trainParam.epochs=2500
net.trainParam.goal=0.001
net.trainParam.show=50
net=train(net,p,t)
r=sim(net,p)
plot(p,t,p,r, * )
y=sim(net,[1.2])
- 2012-04-26 12:14:11下载
- 积分：1
