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In this paper, the pattern recognition problem is considered to be composed of two subproblems. The first subproblem is one of abstracting significant features or characteristics from the patterns being dealt with, while the second subproblem is concerned with identifying the pattern which gave rise to a particular set of features (i. e., a decision-making problem). The decision-making system to be discussed is a special purpose digital computer, which simulates a network of threshold elements designed to correctly identify a preselected set of "typical" patterns. In addition to describing the design procedures, methods of feature extraction, and the hardware employed, the resuits of experiments involving several thousand handwritten characters will also be presented.