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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… 
2009
2009
Non-parametric nonlinear system identification: An asymptotic minimum mean squared error estimator
This paper studies the problem of the minimum mean squared error estimator for non-parametric nonlinear system identification. It… 
2008
2008
Adaptive Hinging Hyperplanes
Abstract The model of adaptive hinging hyperplanes (AHH) is proposed in this paper for black-box modeling. It is based on… 
2007
2007
A comparative study on global wavelet and polynomial models for non-linear regime-switching systems
A comparative study of wavelet and polynomial models for non-linear Regime-Switching (RS) systems is carried out. RS systems… 
2006
2006
A Joint Stochastic Gradient Algorithm and Its Application to System Identification with RBF Networks
Mean-square-error (MSE) and minimum-error-entropy (MEE) criteria play significant roles in adaptive filtering and learning theory… 
Review
2004
Review
2004
Advances in Nonlinear System Identification
The recent approaches in nonlinear system identification are surveyed. T he multi-level recursive identification method and some… 
2003
2003
Hierarchical fuzzy models within the framework of orthonormal basis functions and their application to bioprocess control
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… 
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… 
1991
1991
Recurrent multilayer perceptron for nonlinear system identification
A hybrid feedforward/feedback neural network, namely a recurrent multilayer perceptron, is used to identify nonlinear dynamic… 
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