  Tomograms, a generalization of the Radon transform to arbitrary pairs of
non-commuting operators, are positive bilinear transforms with a rigorous
probabilistic interpretation which provide a full characterization of the
signal and are robust in the presence of noise. Tomograms based on the
time-frequency operator pair, were used in the past for component separation
and denoising. Here we show how, by the construction of an operator pair
adapted to the signal, meaningful information with good time resolution is
extracted even in very noisy situations.

Data Analysis, Statistics and Probability;Information Retrieval;Numerical Analysis