Adaptive non-linear modeling

TitleAdaptive non-linear modeling
Publication TypeConference Paper
Year of Publication1998
AuthorsDavid, A., and T. Aboulnasr
Conference NameAdvances in Digital Filtering and Signal Processing, 1998 IEEE Symposium on
Pagination126 -129
Date Publishedjun.
Keywordsaccuracy, adaptation process, adaptive filters, adaptive nonlinear modeling, approximation, computational complexity, computational cost, computing requirements, convergence, convergence of numerical methods, FIR filters, manageable cost, nonlinearity, optimal solution, precision, processing time, switched filter bank, switched filters

To obtain an accurate model of a process the adaptation process should allow for an arbitrary accuracy within a given cost. Cost may be measured in terms of processing time or computing requirements. It is well known that to gain a better approximation of a process, the adaptation should be able to model a non-linearity at a desirable precision. Currently, methods that do so achieve their accuracy at a high computational cost. Furthermore, these methods do not guarantee i) optimal solution (neural networks), ii) convergence (extended Kalman filtering), or iii) manageable cost (Volterra systems). In this paper, we offer a simple yet powerful method, a switched filter bank, to this end


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