IDENTIFICATION OF NONLINEAR SYSTEMS USING FIXED BUDGET KERNEL LMS ALGORITHM
Journal Title: Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska - Year 2012, Vol 2, Issue 4
Abstract
In this paper a new version of kernel normalized least mean squares algorithm is applied to identification of nonlinear system. To maintain a fixed amount of support vectors, requisite for practical kernel-based algorithm, a pruning criterion is used. After admitting a new input vector to the dictionary, a least important entry is selected and discarder. A case of nonlinear system identification is presented, proving that algorithm performs well and it can maintain a performance comparable to state-of-the-art algorithms, using smaller number of support vectors.
Authors and Affiliations
Dominik Rzepka, Piotr Otfinowski
Keywords
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