An introduction to the design of pattern recognition devices: course held at the Department for Automation and Information, July 1971, Udine
Introduction to problems connected with pattern recognition, & the problem of finding the multivariate probabiluty densities, which have a specified set of marginals. Illustrates two real pattern recognition devices.
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0-transformation Adaptive Pattern Appendix assumed average binary words Block Boolean functions class of patterns Comp computed cost of classifying described design data digit distributions effective set estimate example Feature Extraction finite number Handprinted Highleyman hyperplane IEEE Trans illustrated index of performance integral geometry joint densities Lainiotis lattice points linear linearly separable located machine marginals means for categorization members of Class methods micro-regions minimaxing multivariate density functions Nc classes Nc discriminant functions NH attributes Nilsson number of attributes obtained optimum parameters pattern classes pattern points Pattern Recognition pattern space Perceptron possible PRD design priori probabilities probability density function problem Proc quadric receptor representative patterns Science and Cybernetics Sebestyen Section selected separation surface set of attributes set of Nc statistically independent step Stochastic Approximation sub-sequence Subsection 5.4 Systems Science templets tern test data Theory tion transformation units of probability unlabelled pattern values zero