Maximum likelihood parameter estimation by simulated annealing

The author presents a method for finding the maximum-likelihood estimates of a set of signal parameters. The algorithm is based on simulated annealing, which is a form of stochastic optimization that has been found to be a powerful technique for solving multidimensional combinatorial optimization problems. He also presents a simulated annealing solution to a typical parameter estimation problem that arises in sensor array processing, and some experimental results are included which demonstrate the power of annealing compared to existing algorithms. It is pointed out that simulated annealing is quite a general optimization procedure and should find a wide range of applications.<
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