  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.
