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motaicanshushibie
这是一个关于模态参数识别的资料，里面有几种关于模态参数识别的方法。(This is a modal parameter identification information, which there are several on the modal parameter identification method.)
- 2010-06-18 16:27:31下载
- 积分：1
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a
说明： MATLAB用法和MATLAB教程：MATLAB用法和MATLAB教程：(Use MATLAB and MATLAB Tutorial: MATLAB and use MATLAB Tutorial:)
- 2009-05-30 11:30:04下载
- 积分：1
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MFE
时间序列模型和预测的MATLAB代码，包含参数的估计方法，数据分布的检测，模型预测的源码(Matlab code for time series modeling and forecast )
- 2012-05-05 17:45:56下载
- 积分：1
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shuzitongxinfangzhen
数字通信系统中，基于MATLAB的几种常见信号的仿真(Digital communication system, based on several common signal MATLAB simulation)
- 2009-05-14 23:24:57下载
- 积分：1
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upf
无迹粒子滤波例程，简单的跟踪应用。无杂波环境下的(Unscented particle filter routine, a simple tracking applications)
- 2010-05-29 09:20:34下载
- 积分：1
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Hamm_dual_rat
一种系统辨识方法。对汉默斯坦ARX模型未知参数的系统辨识(Hammerstein MISG algorithm for Hammerstein ARX models)
- 2014-09-18 09:59:55下载
- 积分：1
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GUI
matlab中图形用户界面的教程，包含ppt及matlab程序(Tutorial of the graphical user interface in MATLAB, including PPT and matlab program)
- 2013-12-02 10:31:57下载
- 积分：1
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CM_MC_PLF
说明： 含分布式电源的半不变量法概率潮流计算程序(Probabilistic Power Flow Computing Program Based on Semi-invariant Method)
- 2021-01-25 11:48:37下载
- 积分：1
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Chapter2_3_Pacejka89_Tyremodel
在进行车辆动力学仿真时，轮胎受力对汽车的平顺性、操纵稳定性和安全性起着重要作用。选择符合实际又便于使用的轮胎模型是建立车辆模型并进行动力学仿真的基础。(In the simulation of vehicle dynamics, the force of tire plays an important role in vehicle ride comfort, handling stability and safety. Choosing the tire model which is practical and easy to use is the foundation of establishing the vehicle model and performing the dynamic simulation.)
- 2020-07-04 00:00:02下载
- 积分：1
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decomp_reconst_WU
Decompose image into subbands (undecimated wavelet), denoise, and recompose again.
fh = decomp_reconst_wavelet(im,Nsc,daub_order,block,noise,parent,covariance,optim,sig)
im : image
Nsc: Number of scales
daub_order: Order of the daubechie fucntion used (must be even).
block: size of neighborhood within each undecimated subband.
noise: image having the same autocorrelation as the noise (e.g., a delta, for white noise)
parent: are we including the coefficient at the central location at the next coarser scale?
covariance: are we considering covariance or just variance?
optim: for choosing between BLS-GSM (optim = 1) and MAP-GSM (optim = 0)
sig: standard deviation (scalar for uniform noise or matrix for spatially varying noise)
Javier Portilla, Univ. de Granada, 3/03
Revised: 11/04
- 2010-08-14 20:29:11下载
- 积分：1
