Selection of input variables for model identification of static nonlinear systems
- 1 June 1996
- journal article
- research article
- Published by Springer Nature in Journal of Intelligent & Robotic Systems
- Vol. 16 (2) , 185-207
- https://doi.org/10.1007/bf00449705
Abstract
No abstract availableKeywords
This publication has 12 references indexed in Scilit:
- Neural Fuzzy Control Systems with Structure and Parameter LearningPublished by World Scientific Pub Co Pte Ltd ,1994
- A fuzzy-logic-based approach to qualitative modelingIEEE Transactions on Fuzzy Systems, 1993
- Improving the convergence of the back-propagation algorithmNeural Networks, 1992
- Identification and control of dynamical systems using neural networksIEEE Transactions on Neural Networks, 1990
- Approximation by superpositions of a sigmoidal functionMathematics of Control, Signals, and Systems, 1989
- Multilayer feedforward networks are universal approximatorsNeural Networks, 1989
- Accelerating the convergence of the back-propagation methodBiological Cybernetics, 1988
- Learning representations by back-propagating errorsNature, 1986
- Pattern Recognition with Fuzzy Objective Function AlgorithmsPublished by Springer Nature ,1981
- A new look at the statistical model identificationIEEE Transactions on Automatic Control, 1974