Description: 好用的。系统辨识中,递推最小二乘估计(RLS)是辨识模型阶次的一个重要的算法。该程序通过实现该算法,得到模型阶次的估计值以及相关参数值。
-refrain. System identification, estimation recursive least squares (RLS) identification model is of the order of an important algorithm. The procedures through the realization of the algorithm, to be the order of the model and estimated value of the relevant parameters. Platform: |
Size: 109568 |
Author:叶梭 |
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Description: BP神经网络已广泛应用于非线性建摸、函数逼近、系统辨识等方面,但对实际问题,其模型结构需由
实验确定,无规律可寻。简要介绍了利用 Matlab语言进行 BP网络建立、训练、仿真的方法及注意事项。 -BP neural network has been widely used in nonlinear modeling, function approximation, system identification, etc., but the practical problems, the model structure required by the experiment, if there is no law to be found. Briefly introduce the use of Matlab language BP networks, training, simulation methods and Cautions. Platform: |
Size: 93184 |
Author:覃亮朋 |
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Description: The subject of this book covers three different specific academic areas:
Nonlinear systems, adaptive filtering and system identification. Platform: |
Size: 2873344 |
Author:Gurol |
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Description: 基于CMAC的非线性系统动态辨识,选并联辨识的机构-Based on the CMAC nonlinear system dynamic identification, chooses the parallel identification the organization
Platform: |
Size: 1024 |
Author:徐凯 |
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Description: 【1】随机序列产生程序
【2】白噪声产生程序
【3】M序列产生程序
【4】二阶系统一次性完成最小二乘辨识程序
【5】实际压力系统的最小二乘辨识程序
【6】递推的最小二乘辨识程序
【7】增广的最小二乘辨识程序
【8】梯度校正的最小二乘辨识程序
【9】递推的极大似然辨识程序
【10】Bayes辨识程序
【11】改进的神经网络MBP算法对噪声系统辨识程序
【12】多维非线性函数辨识程序的Matlab程序
【13】模糊神经网络解耦Matlab程序
【14】F-检验法部分程序
-【1】 【2-random sequence generation process white noise generation process】 【3】 M sequence generation process 【4】 to complete a one-time second-order system least-squares identification procedure 【5】 actual pressure system least-squares identification procedure 【6】 Delivery Push the least squares identification procedure augmented 【7】 【8】 least square identification procedures for gradient correction least square identification procedure 【9】 Recursive maximum likelihood identification procedures 【10】 【11】 Bayes identification procedures Improved neural network algorithm MBP noise system identification procedure 【12】 multi-dimensional nonlinear function identification program Matlab program 【13】 fuzzy neural network decoupling Matlab program 【14】 F-test part of the program Platform: |
Size: 7168 |
Author:jshuska |
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Description: Developing Models from Experimental Data using System Identification Toolbox-1. webinar_walk_through.m: contains all the linear and nonlinear estimation examples presented during the webinar.
2. Data files and Simulink models: process_data.mat, ExampleModel.mdl, Friction_Model.mdl. Any other data files used in the presentation already ship with the toolbox (ver 7.0).
Products used:
- You basically need only System Identification Toolbox (SITB) to try out most examples.
- To use Simulink blocks, you would, of course, need Simulink.
- Control System Toolbox is used at one place to show how estimated models can be converted into LTI objects (SS, TF etc)
- Optimization Toolbox will be used if available for grey box estimation. If not, SITB s built-in optimizers will be used automatically.
- Other products mentioned: Neural Network Toolbox, Model Predictive Control Toolbox and Robust Control Toolbox.
Platform: |
Size: 34816 |
Author:陈翼男 |
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Description: 在MATLAB运行环境下,基于支持向量机的非线性系统辨识程序!-Run in the MATLAB environment, based on support vector machines for nonlinear system identification procedure! Platform: |
Size: 83968 |
Author:田红军 |
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Description: 基于神经网络在线辨识的自适应逆振动控制技术。可以有效地应用到非线性系统的控制。-Line identification based on neural network adaptive inverse vibration control technology. Can be effectively applied to nonlinear system control. Platform: |
Size: 14336 |
Author:罗波 |
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Description: Nonlinear System Identification
This demo addresses the use of ANFIS function in the
Fuzzy Logic Toolbox(TM) for nonlinear dynamical system identification.
This demo also requires the System Identification Toolbox(TM), as a comparison is made
between a nonlinear ANFIS and a linear ARX model.
Copyright 1994-2007 The MathWorks, Inc.
$Revision: 1.9.2.4 $- Nonlinear System Identification
This demo addresses the use of ANFIS function in the
Fuzzy Logic Toolbox(TM) for nonlinear dynamical system identification.
This demo also requires the System Identification Toolbox(TM), as a comparison is made
between a nonlinear ANFIS and a linear ARX model.
Copyright 1994-2007 The MathWorks, Inc.
$Revision: 1.9.2.4 $ Platform: |
Size: 17408 |
Author:Mohammed |
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Description: 基于BP算法的神经网络对一个非线性系统进行辨识,最终辨识达到稳定并有较小的辨识误差。-BP neural network algorithm is based on a nonlinear system identification, and ultimately to identify stable and has a small identification error. Platform: |
Size: 589824 |
Author:DelYoung |
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