A differential evolution algorithm for optimizing signal compression and reconstruction transforms
Abstract. State-of-the-art image compression and reconstruction techniques utilize wavelets. Beginning in 2004, however, a team of researchers at Wright-Patterson Air Force Base (WPAFB), the University of Alaska Anchorage (UAA), and the Air Force Institute of Technology (AFIT) has demonstrated that...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.1085.4414 2023-05-15T15:01:19+02:00 A differential evolution algorithm for optimizing signal compression and reconstruction transforms Frank Moore Brendan Babb The Pennsylvania State University CiteSeerX Archives 2008 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1085.4414 http://www.cs.bham.ac.uk/%7Ewbl/biblio/gecco2008/docs/p1907.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1085.4414 http://www.cs.bham.ac.uk/%7Ewbl/biblio/gecco2008/docs/p1907.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.cs.bham.ac.uk/%7Ewbl/biblio/gecco2008/docs/p1907.pdf text 2008 ftciteseerx 2020-05-03T00:32:29Z Abstract. State-of-the-art image compression and reconstruction techniques utilize wavelets. Beginning in 2004, however, a team of researchers at Wright-Patterson Air Force Base (WPAFB), the University of Alaska Anchorage (UAA), and the Air Force Institute of Technology (AFIT) has demonstrated that a genetic algorithm (GA) is capable of evolving non-wavelet transforms that consistently outperform wavelets when applied to a broad class of images under conditions subject to quantization error. Unfortunately, the computational cost of our GA-based approach has been enormous, necessitating hundreds of hours of CPU time, even on supercomputers provided by the Arctic Region Supercomputer Center (ARSC). The purpose of this investigation was to begin to determine whether an alternative approach based upon differential evolution (DE) Text Arctic Alaska Unknown Anchorage Arctic |
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English |
description |
Abstract. State-of-the-art image compression and reconstruction techniques utilize wavelets. Beginning in 2004, however, a team of researchers at Wright-Patterson Air Force Base (WPAFB), the University of Alaska Anchorage (UAA), and the Air Force Institute of Technology (AFIT) has demonstrated that a genetic algorithm (GA) is capable of evolving non-wavelet transforms that consistently outperform wavelets when applied to a broad class of images under conditions subject to quantization error. Unfortunately, the computational cost of our GA-based approach has been enormous, necessitating hundreds of hours of CPU time, even on supercomputers provided by the Arctic Region Supercomputer Center (ARSC). The purpose of this investigation was to begin to determine whether an alternative approach based upon differential evolution (DE) |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Frank Moore Brendan Babb |
spellingShingle |
Frank Moore Brendan Babb A differential evolution algorithm for optimizing signal compression and reconstruction transforms |
author_facet |
Frank Moore Brendan Babb |
author_sort |
Frank Moore |
title |
A differential evolution algorithm for optimizing signal compression and reconstruction transforms |
title_short |
A differential evolution algorithm for optimizing signal compression and reconstruction transforms |
title_full |
A differential evolution algorithm for optimizing signal compression and reconstruction transforms |
title_fullStr |
A differential evolution algorithm for optimizing signal compression and reconstruction transforms |
title_full_unstemmed |
A differential evolution algorithm for optimizing signal compression and reconstruction transforms |
title_sort |
differential evolution algorithm for optimizing signal compression and reconstruction transforms |
publishDate |
2008 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1085.4414 http://www.cs.bham.ac.uk/%7Ewbl/biblio/gecco2008/docs/p1907.pdf |
geographic |
Anchorage Arctic |
geographic_facet |
Anchorage Arctic |
genre |
Arctic Alaska |
genre_facet |
Arctic Alaska |
op_source |
http://www.cs.bham.ac.uk/%7Ewbl/biblio/gecco2008/docs/p1907.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1085.4414 http://www.cs.bham.ac.uk/%7Ewbl/biblio/gecco2008/docs/p1907.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766333344423870464 |