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APPENDIX A Discussion of SingleLayer Network Adaption
BASIC CONCEPTS AND METHODS OF ANALYSIS
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adaptive element adaptive linear threshold adaptive network adaptive pattern adaptive system adaptive threshold elements adaptive-element adaptive-network solutions analog sum analysis average percent configuration completely equivalent dead zone degree of equivalence desired output E[cos 9 expected value experimental data extrapolative ability extrapolative characteristics function hyperplanes determined hypersphere-area approximation input patterns intersection Koford l-E[cos linear threshold element linearly separable logic gate lune of angle N.Y. l Attn negative patterns network output networks of adaptive number of patterns number of training output q PARITY-gate network pattern vectors patterns to twice percent configuration agreement positive patterns positive-pattern Pr[Y problem proportionality constant reference network reference system reference-adaptive structure reference-element weight vector shown in Fig single adaptive single linear threshold single threshold element single-layer network solution cone solution weight vector spherical triangle statistical population test patterns training patterns training set two-element network two-element OR-gate network uniform distribution unit hypersphere Variation of average