• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1793-1801
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• 2015

In a recent work, kernel recursive least-squares tracker (KRLS-T) algorithm has been proposed. It is capable of tracking in non-stationary environments using a forgetting mechanism built on a Bayesian framework. The forgetting mechanism in KRLS-T is implemented by a fixed forgetting factor. In practice, however, we frequently meet that the fixed forgetting factor cannot handle time-varying system effectively. In this paper we propose a new KRLS-T with a variable forgetting factor. Experimental results show that proposed algorithm can handle time-varying system more effectively than the KRLS-T.