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mm1_example
The queueing example which is simplest for mathematical analysis is the M/M/1 queue. Here is the tcl script for it.
- 2013-12-20 00:53:39下载
- 积分:1
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123waveletNeuralNetworks
本程序主要用于小波神经网络电力负荷预测。(This procedure is mainly used for wavelet neural network power load forecasting)
- 2017-09-02 21:11:04下载
- 积分:1
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bayesgauss
图像处理MATLAB源代码,这个是贝叶斯估计-bayes guess(Image Processing MATLAB source code, this is the Bayesian estimation-bayes guess)
- 2013-11-13 14:47:46下载
- 积分:1
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singal_system_analysis
该程序是基于MATLAB编写的对信号进行分析的随机信号通过线性系统,包括时域、频域等多项分析(signal and system analysis)
- 2009-09-12 10:11:30下载
- 积分:1
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Jacobi
雅克比迭代法 求Hilbert矩阵病态方程组(Iterative Method Jacobian matrix pathological Hilbert equations)
- 2009-05-23 20:16:26下载
- 积分:1
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lvboqi_shiyan
巴特霍兹带通滤波器,可以通过不同的ws、wp实验出自己需要的频带(buttord filter)
- 2011-06-01 16:52:21下载
- 积分:1
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floydwarshall
采用floyd算法计算图中任意两点之间最短路程,可以有负权(Floyd algorithm to calculate the shortest distance between any two points can have a negative right to)
- 2012-04-16 14:40:41下载
- 积分:1
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chmmbox_1_2
CHMMBOX, version 1.2, Iead Rezek, Oxford University, Feb 2001
Matlab toolbox for max. aposteriori estimation of two chain
Coupled Hidden Markov Models.
(CHMMBOX, version 1.2, Iead Rezek, Oxford University, Feb 2001 Matlab toolbox for max. aposteriori es timation of two chain Coupled Hidden Markov Mod els.)
- 2007-03-26 22:29:08下载
- 积分:1
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xox_Wave_NN
The Wavelet Neural Network
This is simple example for using of modified Morlet neural network.
Levenberg-Marquardt with numerical Jacobian calculation implemented.
Easy to use with other optimization algorithem e.g GA,PSO, etc.
The function "xox_lm" may be useful for other optimization problem easily.
The function "xox_jacobian" may be useful for Jacobian calculation easily.
The function "NN_fcn" may be used by the evolutionary based neural network.
The activation function "modified Morlet" will be replaceable by others.
- 2013-07-12 17:31:12下载
- 积分:1
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11912871JPEGanJPEG2000final
Numerical mtd is used for calculating the diflection of the structure
- 2010-02-08 16:39:09下载
- 积分:1