Noise Reduction in Chaotic Signals by Using Wiener and Kalman Filtering Methods

Abstract

In this paper, the additive white noise was filtered from chaotic signals obtained by logistic map by using Wiener, extended and unscented Kalman filters, respectively. Performances of each method were compared by finding mean square error versus signal to noise ratio (SNR) and correlation dimension which is one of the invariants of the chaotic dynamical systems. It was observed that, each method exhibits different MSE performances depending on the particular signal to noise ratio.