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MemristorModel

于 2021-04-20 发布文件大小:1403KB

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下载积分: 1 下载次数: 172

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代码说明：

忆阻器的matlab 仿真模型，含一个simulink 模型和M语言代码(Matlab code for memristor, including a simulink model and a matlab routine)

文件列表：

MemristorModel
..............\i-v.fig,396773,2009-08-20

..............\i_v_flux_of_memristor.mdl,44277,2009-08-21
..............\license.txt,1337,2009-08-20
..............\q-flux.fig,925965,2009-08-21

..............\Run_Simulation_Memristor.m,3956,2009-08-21

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Matlab
说明：有用的MATLAB源码，关于有限元部分的，对于不使用cae商业软件需自编程的人员，有很好的指导作用(Useful MATLAB source code, on the finite element part, for non-use of cae commercial software required to self-programming personnel, have a good guide)

2010-03-25 18:43:41下载

积分：1
jiqirenxueshiyan
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2010-06-13 23:53:42下载

积分：1
commonclusteringarilothm
常好的聚类工具包,用Matlab开发,适合于科研用途等.ZIP(CLUSTERING)

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matlab code for LOLIMOT algorithm

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时频分析中的Wigner-Ville方法函数(Time-frequency analysis of the Wigner-Ville method function)

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基于AR参数模型的功率谱估计及其结果分析(Based on the AR parameter model of the power spectrum estimation and Results Analysis)

2013-04-18 16:35:39下载

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ridgew
自己写的岭回归算法。做统计的都懂得。有需要就自己下载(Write your own regression algorithm. All know how to do statistics. There is a need to download)

2020-07-04 09:40:01下载

积分：1
ST
说明： S变换是较新的时频分析工具，甩在低频段有较宽的的时间窗，以获得较高的频率分辨率；而在高频段时间窗窄，以获得较高的时间分辨率。这里给出了ST和GST（广义S变换）的函数。(S transform is a relatively new time-frequency analysis tool, left in the low frequency band has a wide time window in order to obtain higher frequency resolution and in high-frequency narrow time window in order to obtain higher temporal resolution. Here are given ST and GST (generalized S transform) function.)

2008-02-18 18:37:05下载

积分：1
MATLAB-basic
基于matlab的一些常用算法，包括一些数值算法，特殊函数的计算等(Based on matlab some commonly used algorithms, including some of the numerical algorithm, the calculation of the special function)

2013-01-22 11:29:30下载

积分：1
rjMCMCsa
可逆跳跃马尔科夫蒙特卡洛贝叶斯模型选择，主要用于神经网络(Reversible Jump MCMC Bayesian Model Selection This demo demonstrates 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.)

2013-03-11 22:29:52下载

积分：1

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MemristorModel

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