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ztfx
电力系统动态稳定性分析程序，matlab编写，代码精简，功能强悍(Power system dynamic stability analysis program, matlab write, code streamlining, powerful functions)
- 2011-10-21 15:55:19下载
- 积分：1
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lunwen
最新关于故障诊断的论文，有LMD算法，还有EMD算法，主要是做轴承磨损预测的(failed to translatefailed to translatefailed to translatefailed to translate)
- 2013-05-03 10:47:38下载
- 积分：1
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matlab
简单的if else，和switch分支的小程序，希望大家谅解(Simple if else, and switch branches applet, I hope you understand)
- 2013-05-22 15:10:36下载
- 积分：1
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OFDM__explaination
orthogonal frequency division multiplexing using wireless networks
- 2010-12-17 00:07:39下载
- 积分：1
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pss
pss control for synchronous machin
- 2010-12-18 22:29:11下载
- 积分：1
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Papers-in-WiMAX
Seamless Handover between WiMAX and UMTS.
- 2011-02-12 01:58:54下载
- 积分：1
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MATlAB
说明： 应用MATlAB语言处理数字信号与数字图像(Application MATlAB language processing digital signals and digital images)
- 2010-04-25 21:07:24下载
- 积分：1
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journal-v-finale
a good reference for study synchronization in wireless sensors networks
- 2013-11-03 00:13:30下载
- 积分：1
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用于绘制SW模型下的磁滞回线
说明： 用于绘制SW模型下的磁滞回线，可以改变磁场的方向和大小，在铁磁学中常用。(Drawing hysteresis loop under SW model can change magnetic field angle and size. Commonly used in ferromagnetism)
- 2019-11-30 21:06:51下载
- 积分：1
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Reversible_Jump_MCMC_Bayesian_Model_Selection
This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
(This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
)
- 2008-03-07 23:23:12下载
- 积分：1
