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Qcar-PID
A PID Control for Improving the characteristics of a Quarter model of a car suspension
- 2009-07-01 20:44:03下载
- 积分：1
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svpwm2
空间电压矢量调制技术模块，进过自己认真仔细的搭建，可用。(Space vector modulation module, has been to carefully build available.)
- 2012-05-19 20:56:09下载
- 积分：1
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ImageFusion
图像融合工具包
用matlab实现
(MATLAB Image Fusion Toolkit)
- 2009-05-12 10:11:32下载
- 积分：1
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MatLab_commands
Matlab常用命令集合，包括科学计算和图形图像处理的命令等，方便查阅(Matlab a collection of commonly used commands, including scientific computing and graphics image processing orders, for easy access)
- 2010-01-18 21:01:41下载
- 积分：1
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gauss
说明： gauss积分matlab代码，一个完整的程序(matlab code gauss points, a complete program)
- 2011-04-09 02:08:40下载
- 积分：1
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Constrain_Fuzzy_model_identification
Constrain Fuzzy model identification的学习文件以及其模拟的源码。(Include "Constrain Fuzzy model identification" learning document and simulation matlab code.)
- 2010-07-06 18:27:49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
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IIR
IIR数字通信滤波器的设计源程序与实现过程(IIR Digital Communication Filter Design and Implementation of source code)
- 2009-11-16 18:58:31下载
- 积分：1
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toolbox_tensor_voting
张量投票在matlab环境下的仿真。球型张量及棒型张量的仿真(Tensor voting in matlab simulation environment. Spherical and rod-type tensor tensor Simulation)
- 2009-05-22 18:03:14下载
- 积分：1
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inverter-control
inverter control pwm technique
- 2014-10-27 18:57:10下载
- 积分：1
