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Article: A new hybrid descent method with application to the optimal design of finite precision FIR filters

TitleA new hybrid descent method with application to the optimal design of finite precision FIR filters
Authors
KeywordsFinite Precision
Fir Filter Design
Hybrid Descent Method
Simulating Annealing
Issue Date2010
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/10556788.asp
Citation
Optimization Methods And Software, 2010, v. 25 n. 5, p. 725-735 How to Cite?
AbstractIn this paper, the problem of the optimal design of discrete coefficient FIR filters is considered. A novel hybrid descent method, consisting of a simulated annealing algorithm and a gradient-based method, is proposed. The simulated annealing algorithm operates on the space of orthogonal matrices and is used to locate descent points for previously converged local minima. The gradient-based method is derived from converting the discrete problem to a continuous problem via the Stiefel manifold, where convergence can be guaranteed. To demonstrate the effectiveness of the proposed hybrid descent method, several numerical examples show that better discrete filter designs can be sought via this hybrid descent method. © 2010 Taylor & Francis.
Persistent Identifierhttp://hdl.handle.net/10722/155927
ISSN
2015 Impact Factor: 0.841
2015 SCImago Journal Rankings: 1.063
ISI Accession Number ID
Funding AgencyGrant Number
Research Grants Council of HKSARPolyU 7191/06E
Research Committee of the Hong Kong Polytechnic University
Funding Information:

This research was supported by the Research Grants Council of HKSAR (PolyU 7191/06E) and the Research Committee of the Hong Kong Polytechnic University. We would like to thank the anonymous referees for their constructive comments.

References

 

DC FieldValueLanguage
dc.contributor.authorYiu, KFCen_US
dc.contributor.authorYan, WYen_US
dc.contributor.authorTeo, KLen_US
dc.contributor.authorLow, SYen_US
dc.date.accessioned2012-08-08T08:38:27Z-
dc.date.available2012-08-08T08:38:27Z-
dc.date.issued2010en_US
dc.identifier.citationOptimization Methods And Software, 2010, v. 25 n. 5, p. 725-735en_US
dc.identifier.issn1055-6788en_US
dc.identifier.urihttp://hdl.handle.net/10722/155927-
dc.description.abstractIn this paper, the problem of the optimal design of discrete coefficient FIR filters is considered. A novel hybrid descent method, consisting of a simulated annealing algorithm and a gradient-based method, is proposed. The simulated annealing algorithm operates on the space of orthogonal matrices and is used to locate descent points for previously converged local minima. The gradient-based method is derived from converting the discrete problem to a continuous problem via the Stiefel manifold, where convergence can be guaranteed. To demonstrate the effectiveness of the proposed hybrid descent method, several numerical examples show that better discrete filter designs can be sought via this hybrid descent method. © 2010 Taylor & Francis.en_US
dc.languageengen_US
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/10556788.aspen_US
dc.relation.ispartofOptimization Methods and Softwareen_US
dc.subjectFinite Precisionen_US
dc.subjectFir Filter Designen_US
dc.subjectHybrid Descent Methoden_US
dc.subjectSimulating Annealingen_US
dc.titleA new hybrid descent method with application to the optimal design of finite precision FIR filtersen_US
dc.typeArticleen_US
dc.identifier.emailYiu, KFC:cedric@hkucc.hku.hken_US
dc.identifier.authorityYiu, KFC=rp00206en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1080/10556780903254104en_US
dc.identifier.scopuseid_2-s2.0-77953503618en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77953503618&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume25en_US
dc.identifier.issue5en_US
dc.identifier.spage725en_US
dc.identifier.epage735en_US
dc.identifier.isiWOS:000278706700005-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridYiu, KFC=24802813000en_US
dc.identifier.scopusauthoridYan, WY=7402221751en_US
dc.identifier.scopusauthoridTeo, KL=35569785000en_US
dc.identifier.scopusauthoridLow, SY=15061436400en_US

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