Abstract
A solution for achieving blind separation for underdetermined systems is to use an overcomplete basis function set that has the ability to span all possible inputs. Ideally, such a basis would be learned for each set of inputs but this is computationally expensive. A less processor intensive system is shown using a fixed dictionary of basis functions learned from existing sources and reduced using a correlation-based method. The relation between dictionary size and separation performance for underdetermined scenarios is examined and we demonstrate that a reduced dictionary can produce comparable results using less computational power.
Translated title of the contribution | Blind signal separation using fixed overcomplete basis function dictionaries |
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Original language | English |
Title of host publication | 2003 International Symposium on Circuits and Systems, 2003 (ISCAS '03) |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | III-44 - III-47 |
Number of pages | 4 |
Volume | III |
ISBN (Print) | 0780377613 |
DOIs | |
Publication status | Published - May 2003 |
Event | International Symposium on Circuits and Systems, 2003 - Bangkok, Thailand Duration: 1 May 2003 → … |
Conference
Conference | International Symposium on Circuits and Systems, 2003 |
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Abbreviated title | ISCAS '03 |
Country/Territory | Thailand |
City | Bangkok |
Period | 1/05/03 → … |
Bibliographical note
Rose publication type: Conference contributionSponsorship: The authors would like to thank the support from the U.K. MOD TGOl CRP Fellowship project.
Terms of use: Copyright © 2003 IEEE. Reprinted from 2003 International Symposium on Circuits and Systems, 2003 (ISCAS '03).
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