Open AccessSignal recognition and adapted filtering by non‐commutative tomography
Author(s) -
Aguirre Carlos,
Mendes Rui Vilela
Publication year - 2014
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/iet-spr.2012.0227
Subject(s) - computer science , artificial intelligence , pattern recognition (psychology) , signal (programming language) , tomography , signal processing , commutative property , speech recognition , computer vision , algorithm , mathematics , digital signal processing , physics , pure mathematics , computer hardware , optics , programming language
Tomogram, a generalisation of the Radon transform to arbitrary pairs of non‐commuting operators, is a positive bilinear transforms with a rigorous probabilistic interpretation which provides a full characterisation of the signal and is 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 the authors show that, even for noisy signals, meaningful time‐resolved information may be obtained by the construction of an operator pair adapted to the signal.