A. V. Merkusheva
Saint-Petersburg
A method is given for nonstationary signal filtering in wavelet-mapping
domain for information-measurement systems. The method is based on the
statistical wavelet coefficients (WC) distribution for signals and noise
of different types and dynamic adaptation to their nonstationary properties.
We obtained the WC probability distribution in the form of exponential
law and determined its parameters. We also expressed analytically the dependence
of the WC discrimination threshold on WC distribution parameters and on
the noise type and power. This makes more precise Donoho and Johnstone's
results. At the same time the expression for the WC discrimination threshold
is a generalization of Cramer's formula which assumed a Gauss distribution.
A speech signal and four types of noise were used as a general form of
nonstationary signal.