Noise reduction for flows using nonlinear constraints

Abstract

On the basis of a local-projective with nonlinear constraints (LPNC) approach (see K. Urbanowicz, J.A. Holyst, T. Stemler and H. Benner, Acta Phys. Pol B 35 (9), 2175, 2004) we develop a method of noise reduction in time series that makes use of constraints appearing due to the continuous character of flows. As opposed to local-projective methods in our method we do not need to determine the Jacobi matrix. The approach has been successfully applied for separating a signal from noise in the Lorenz model and in noisy experimental data obtained from an electronic Chua circuit. The method was then applied for filtering noise in human voice.