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Nonlinear system identification

System identification is a method of identifying or measuring the mathematical model of a system from measurements of the system inputs and outputs… 
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Related topics

Related topics

19 relations
ApproximationArtificial neural networkBifurcation theoryBig data

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2012
2012
Exact Penalty and Optimality Condition for Nonseparable Continuous Piecewise Linear Programming
Utilizing compact representations for continuous piecewise linear functions, this paper discusses some theoretical properties for… 
2010
2010
A novel adaptive bilinear filter based on pipelined architecture
2008
2008
Gas-liquid separator modelling and simulation with Gaussian-process models
2003
2003
Hierarchical fuzzy models within the framework of orthonormal basis functions and their application to bioprocess control
Review
2002
Review
2002
Nonlinear Identification and Control: A Neural Network Approach [Book Review]
2001
2001
Speaker Auralization ' Subjective Evaluation of Nonlinear Distortion
Wolfgang Klippel Klippel GmbH Germany www.klippel.de ABSTRACT A new auralization technique is presented for the objective and… 
1998
1998
Adaptive control of first-order systems with nonlinear parameterization
An adaptive control method is presented for a class of first-order systems with nonlinear parametrization. The main feature of… 
Review
1996
Review
1996
Nonlinear system identification using neural networks
In this Chapter we treat the problem of nonlinear system identification using neural networks. Model structures and their… 
1995
1995
Nonlinear system identification for control using Volterra-Laguerre expansion
The large number of parameters needed to represent the kernels is the major criticism in using Volterra series as nonlinear… 
1994
1994
Sampling frequency requirements for identification and compensation of nonlinear systems
Nonlinear systems usually cause spectral spreading resulting in an output signal bandwidth that is greater than the input signal… 
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