A pattern recognition application of the ALOPEX process with hexagonal arrays

The ALOPEX process is a broadly defined optimization procedure which simultaneously varies several parameters based on single value feedback and noise application, ALOPEX is used to solve an image recognition problem using several hexagonally based templates. Efficiency improvements are examined, such as a 'temperature' effect, arrival at optimal parameter values, and a form of parallelization. Two different forms of the 'cost' function are analyzed, and a hierarchical system is attempted to attain faster 'good' solutions. The analysis is expanded to multiple template simulations, where the algorithm is able to make appropriate recognition decisions on noisy or incomplete data.<
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