Signal processing applications using adaptive simulated annealing

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)