Open AccessTree‐structured complex wavelet‐based Bayesian compressive sensing method
Author(s) -
Sadeghigol Z.,
Kahaei M.H.,
Haddadi F.
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2013.2300
Subject(s) - wavelet , bayesian probability , pattern recognition (psychology) , compressed sensing , tree (set theory) , computer science , artificial intelligence , algorithm , spike (software development) , mathematics , scale (ratio) , statistics , physics , mathematical analysis , software engineering , quantum mechanics
Using complex wavelets, the tree‐structured complex wavelet Bayesian compressive sensing method is proposed. The hidden Markov tree is used for inter‐scale relations of wavelet coefficients. The spike‐slab distribution is considered for the prior. From simulation results, the number of measurements and the value of reconstruction error reduce by 25% and 65%, respectively.