A novel adaptive filter algorithm for tracking of chaotic time series

In this study, a novel tracking filter algorithm is proposed satisfying stability in the sense of Lyapunov and is performed which is independent of statistical properties of input. The robustness of the proposed filter is presented by using two benchmark chaotic time series found in the literature. The proposed filter is compared with well known classical filters and performed in a high performance.