Estimation of signal and noise spectra by special averaging techniques with application to a posteriori "Wiener" filtering.

This paper deals with the problem of separating the spectra of signal and noise in ensembles where the signal can be considered as an invariant component and the noise as a stationary additive background. Several methods are discussed and compared on the basis of a statistical analysis of the first two moments of the estimators for signal and noise spectra. As a consequence a procedure is proposed which provides a flexible compromise between estimation accuracy and computational effort. The application of this procedure to a posteriori "Wiener" filtering is compared with a more common, but time consuming, technique.