IDENTIFICATION OF NONLINEAR SYSTEMS USING FIXED BUDGET KERNEL LMS ALGORITHM

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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  • EP ID EP59394
  • DOI -
  • Views 113
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How To Cite

Dominik Rzepka, Piotr Otfinowski (2012). IDENTIFICATION OF NONLINEAR SYSTEMS USING FIXED BUDGET KERNEL LMS ALGORITHM . Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska, 2(4), 10-13. https://europub.co.uk/articles/-A-59394