TY - JOUR
T1 - Adaptive simulated annealing for optimization in signal processing applications
AU - Chen, S.
AU - Luk, B. L.
PY - 1999/11
Y1 - 1999/11
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 optimization problems. Three applications, maximum likelihood (ML) joint channel and data estimation, infinite-impulse-response (IIR) filter design and evaluation of minimum symbol-error-rate (MSER) decision feedback equalizer (DFE), are used to demonstrate the effectiveness of the ASA.
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 optimization problems. Three applications, maximum likelihood (ML) joint channel and data estimation, infinite-impulse-response (IIR) filter design and evaluation of minimum symbol-error-rate (MSER) decision feedback equalizer (DFE), are used to demonstrate the effectiveness of the ASA.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0033316827&origin=recordpage
U2 - 10.1016/S0165-1684(99)00084-5
DO - 10.1016/S0165-1684(99)00084-5
M3 - RGC 21 - Publication in refereed journal
SN - 0165-1684
VL - 79
SP - 117
EP - 128
JO - Signal Processing
JF - Signal Processing
IS - 1
ER -