Adaptive simulated annealing for optimization in signal processing applications

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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