Time-frequency methods and phase space are as well known to most physicists, engineers and mathematicians as traditional Fourier analysis, which has recently found for many applications a competitor in the concept of wavelets. Crudely speaking a wavelet decomposition is an expansion of an arbitrary function into smooth localized contributions labeled by a scale and a position parameter. The meeting recorded in this volume brought together people exploring and applying these concepts in an interdisciplinary framework. Topics discussed range from purely mathematical aspects to signal and speech analysis, seismic and acoustic applications, and wavelets in computer vision.