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Neural networks with cellular atrophy for geometric database classifications

In this paper we examine the use of geometric modeling in grouping and classification. A neural network approach is suggested to combine the completeness of information provided by a geometric modeler with the uncertainty required in the grouping process. The utilization of highly connectionist systems in such an environment is investigated. The advantages and shortcomings of these systems are discussed. The impact of cellular atrophy, as observed in biological systems, on highly connectionist systems is proposed. The effect of atrophy criterion on systems' size and efficiency is examined.