NDLI: Selecting inputs and measuring nonlinearity in system identification

Content Provider	IEEE Xplore Digital Library
Author	Poncet, A. Moschytz, G.S.
Copyright Year	1996
Description	Author affiliation: Swiss Federal Inst. of Technol., Zurich, Switzerland (Poncet, A.; Moschytz, G.S.)
Abstract	The problems of selecting inputs and measuring system nonlinearity are stated in terms of statistical estimation theory The natural solution which emerges consists in estimating and comparing Bayes risk (minimum mean square error) with the linear minimum risk. For any subset of inputs, these quantities are defined as the overall best performance achievable using a nonlinear and a linear model, respectively. A method based on kernel density estimation is presented to compute both quantities directly from a batch of input-output data, prior to any model choice. The relevance of a particular input subset can thus be naturally quantified by its corresponding minimum risk. As a consequence, superfluous input variables can, in principle, be detected and removed before the tedious task of model structure design, Furthermore, the method enables to determine a priori the improvement which can potentially be achieved by using a nonlinear model instead of a linear one. In practice, the method is limited by the required amount of data increasing exponentially with the number of inputs, which is characteristic of nonparametric estimation techniques.
Starting Page	2
Ending Page	10
File Size	540213
Page Count	9
File Format	PDF
ISBN	0818674563
DOI	10.1109/NICRSP.1996.542739
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-08-21
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Input variables Mean square error methods Estimation theory Information processing Signal processing Multilayer perceptrons Turning Polynomials System identification Kernel
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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