In this paper, we present an approach to system identification based on viewing identification as a problem in statistical learning theory. Apparently, this approach was first mooted in [E. Weyer, R.C. Williamson, I. Mareels, Sample complexity of least squares identification of FIR models, in: Proce
An adaptive learning approach to the identification of structural and mechanical systems
β Scribed by Robert E. Kalaba; Firdaus E. Udwadia
- Publisher
- Elsevier Science
- Year
- 1991
- Tongue
- English
- Weight
- 593 KB
- Volume
- 22
- Category
- Article
- ISSN
- 0898-1221
No coin nor oath required. For personal study only.
β¦ Synopsis
Abetract--The identification of parameters in mode I,, of structural and mechanical systems k an important problem. The usual approaches are sncccaaive approximation ,Β’..hemes which require good initial guesacs for rapid convergence. Thk paper show. how such initial approximatiorm may be obtained. Notiona from the field oi artificial neural network, are uaed. In fact, new adaptive achem~ for learning are prmcnted and used in parameter Β’atimation for both linear and nonlinear .y.tem~.
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