Signal processing applications using adaptive simulated annealing

S. Chen; R. H. Istepanian; B. L. Luk

doi:10.1109/CEC.1999.782510

Signal processing applications using adaptive simulated annealing

S. Chen, R. H. Istepanian, B. L. Luk

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

6 Citations (Scopus)

Abstract

Many signal processing applications pose optimization problems with multimodal and nonsmooth cost functions. Gradient methods are ineffective in these situations. The adaptive simulated annealing (ASA) offers a viable optimization tool for tackling these difficult nonlinear problems. We demonstrate the effectiveness of the ASA using three applications, infinite-impulse-response (IIR) filter design, maximum likelihood (ML) joint channel and data estimation and evaluation of minimum symbol-error-rate (MSER) decision feedback equalizer (DFE). © 1999 IEEE.

Original language	English
Title of host publication	Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999
Publisher	IEEE Computer Society
Pages	842-849
Volume	2
DOIs	https://doi.org/10.1109/CEC.1999.782510
Publication status	Published - 1999
Externally published	Yes
Event	1999 Congress on Evolutionary Computation (CEC 1999) - Mayflower Hotel, Washington, DC, United States Duration: 6 Jul 1999 → 9 Jul 1999

Publication series

Name
Volume	2

Conference

Conference	1999 Congress on Evolutionary Computation (CEC 1999)
Place	United States
City	Washington, DC
Period	6/07/99 → 9/07/99

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10.1109/CEC.1999.782510

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title = "Signal processing applications using adaptive simulated annealing",

abstract = "Many signal processing applications pose optimization problems with multimodal and nonsmooth cost functions. Gradient methods are ineffective in these situations. The adaptive simulated annealing (ASA) offers a viable optimization tool for tackling these difficult nonlinear problems. We demonstrate the effectiveness of the ASA using three applications, infinite-impulse-response (IIR) filter design, maximum likelihood (ML) joint channel and data estimation and evaluation of minimum symbol-error-rate (MSER) decision feedback equalizer (DFE). {\textcopyright} 1999 IEEE.",

author = "S. Chen and Istepanian, {R. H.} and Luk, {B. L.}",

year = "1999",

doi = "10.1109/CEC.1999.782510",

language = "English",

volume = "2",

publisher = "IEEE Computer Society",

pages = "842--849",

booktitle = "Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999",

address = "United States",

note = "1999 Congress on Evolutionary Computation (CEC 1999) ; Conference date: 06-07-1999 Through 09-07-1999",

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Chen, S, Istepanian, RH & Luk, BL 1999, Signal processing applications using adaptive simulated annealing. in Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999. vol. 2, 782510, IEEE Computer Society, pp. 842-849, 1999 Congress on Evolutionary Computation (CEC 1999), Washington, DC, District of Columbia, United States, 6/07/99. https://doi.org/10.1109/CEC.1999.782510

Signal processing applications using adaptive simulated annealing. / Chen, S.; Istepanian, R. H.; Luk, B. L.
Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999. Vol. 2 IEEE Computer Society, 1999. p. 842-849 782510.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Signal processing applications using adaptive simulated annealing

AU - Chen, S.

AU - Istepanian, R. H.

AU - Luk, B. L.

PY - 1999

Y1 - 1999

N2 - Many signal processing applications pose optimization problems with multimodal and nonsmooth cost functions. Gradient methods are ineffective in these situations. The adaptive simulated annealing (ASA) offers a viable optimization tool for tackling these difficult nonlinear problems. We demonstrate the effectiveness of the ASA using three applications, infinite-impulse-response (IIR) filter design, maximum likelihood (ML) joint channel and data estimation and evaluation of minimum symbol-error-rate (MSER) decision feedback equalizer (DFE). © 1999 IEEE.

AB - Many signal processing applications pose optimization problems with multimodal and nonsmooth cost functions. Gradient methods are ineffective in these situations. The adaptive simulated annealing (ASA) offers a viable optimization tool for tackling these difficult nonlinear problems. We demonstrate the effectiveness of the ASA using three applications, infinite-impulse-response (IIR) filter design, maximum likelihood (ML) joint channel and data estimation and evaluation of minimum symbol-error-rate (MSER) decision feedback equalizer (DFE). © 1999 IEEE.

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DO - 10.1109/CEC.1999.782510

M3 - RGC 32 - Refereed conference paper (with host publication)

VL - 2

SP - 842

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BT - Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999

PB - IEEE Computer Society

T2 - 1999 Congress on Evolutionary Computation (CEC 1999)

Y2 - 6 July 1999 through 9 July 1999

ER -

Signal processing applications using adaptive simulated annealing

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