  In this paper we present algorithms for approximating real band-limited
signals by multiple Gaussian Chirps. These algorithms do not rely on matching
pursuit ideas. They are hierarchial and, at each stage, the number of terms in
a given approximation depends only on the number of positive-valued maxima and
negative-valued minima of a signed amplitude function characterizing part of
the signal. Like the algorithms used in \cite{gre2} and unlike previous
methods, our chirplet approximations require neither a complete dictionary of
chirps nor complicated multi-dimensional searches to obtain suitable choices of
chirp parameters.
