Beyond ICA: Robust sparse signal representations

Andrzej Cichocki, Yuanqing Li, Pando Georgiev, Shun Ichi Amari

Research output: Contribution to journalConference articlepeer-review

6 Citations (Scopus)


In many applications it is necessary to perform some decomposition of observed signals or data in such a way that components have some special properties or structures such as statistical independence, sparsity, smoothness, non-negativity, prescribed statistical distributions and/or specific temporal structure. In this paper we discuss cost functions whose minimization solve such problems and we present new properties that characterize optimal solutions for sparse representations. Especially, we discuss robust cost functions in order to find sparse representation of noisy signals. Furthermore, we discuss sub-band decomposition preprocessing to relax independence conditions for source signals.

Original languageEnglish
Pages (from-to)V-684-V-687
JournalProceedings - IEEE International Symposium on Circuits and Systems
Publication statusPublished - 2004
Externally publishedYes
Event2004 IEEE International Symposium on Cirquits and Systems - Proceedings - Vancouver, BC, Canada
Duration: 23 May 200426 May 2004


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