Modeling Hysteresis and Its Inverse Model Using Neural Networks Based on Expanded Input Space Method
- Author
- XINLONG ZHAO1 ; YONGHONG TAN2
[1] Institute of Automation, Zhejiang Sci-Tech University, Hangzhou 310018, China
[2] School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China - Source
IEEE transactions on control systems technology. 2008, Vol 16, Num 3, pp 484-490, 7 p ; ref : 12 ref
- CODEN
- IETTE2
- ISSN
- 1063-6536
- Scientific domain
- Control theory, operational research; Electrical engineering
- Publisher
- Institute of Electrical and Electronics Engineers, New York, NY
- Publication country
- United States
- Document type
- Article
- Language
- English
- Author keyword
- -Hysteresis hysteretic operator inverse model modeling neural networks
- Keyword (fr)
- Fonction multivoque Hystérésis Identification système Matrice inverse Modélisation Problème inverse Réseau neuronal
- Keyword (en)
- Multivalued function Hysteresis System identification Inverse matrix Modeling Inverse problem Neural network
- Keyword (es)
- Función multívoca Histéresis Identificación sistema Matriz inversa Modelización Problema inverso Red neuronal
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02D Control theory. Systems / 001D02D05 Modelling and identification
- Discipline
- Computer science : theoretical automation and systems
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 20317303
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1109/TCST.2007.906274 
https://dx.doi.org/10.1109/TCST.2007.906274
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