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: 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: This addresses the use of ANFIS function in the Fuzzy Logic Toolbox for nonlinear dynamical system identification. This
also requires the System Identification Toolbox, as a comparison is made between a nonlinear ANFIS and a linear ARX model. Platform: |
Size: 4096 |
Author:manoj |
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Description: 各种非线性系统辨识的编程方法，主要是matlab工具箱的使用，以及常规的几种结构模型，有利于非线性系统辨识的朋友-All kinds of nonlinear system identification method of programming, mainly is the use of matlab toolbox, and conventional several structure model, be helpful for nonlinear system identification of friends Platform: |
Size: 3348480 |
Author:sunli |
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Description: 《系统辨识与MATLAB仿真.pdf》 侯媛彬 汪梅 王立琦
本书共分8章，第1、2章为辨识的基本概念、理论基础和古典辨识方法；第3至6章为现代辨识内容，其中第3章是最小二乘参数辨识，第4章是梯度校正参数辨识，第5章是极大似然法的参数辨识方法，第6章是自适应参数辨识；第7、8章为复杂的非线性系统的智能辨识和混沌辨识，其中第7章是非线性系统的神经网络辨识；第8章是Volterra辨识方法、复杂系统的混沌现象及其辨识。从第2至7章，各章均包含开发的相应程序及其程序剖析。
-" System Identification and MATLAB simulation. Pdf" Hou Yuanbin Wang Mei Wang Liqi book is divided into eight chapters, Chapters 1 and 2 for the identification of the basic concepts, theoretical foundation and classical identification methods first 3-6 chapters of modern identification content, Chapter 3 is the least squares parameter identification, Chapter 4 is the gradient correction parameter identification, Chapter 5 is the maximum likelihood parameter identification method, Chapter 6 is an adaptive parameter identification Chapters 7 and 8 for complex Intelligent identification of nonlinear systems and chaos identification, which is in Chapter 7 of the neural network nonlinear system identification Chapter 8 is Volterra identification method, complex systems and chaos identification. From the first 2-7 chapters, each chapter contains procedures for the development of appropriate programs and their analysis. Platform: |
Size: 7103488 |
Author:唐小米 |
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