Download e-book for iPad: Биологические мотивации by Судаков К.В.

By Судаков К.В.

ISBN-10: 1597454443

ISBN-13: 9781597454445

ISBN-10: 1934115118

ISBN-13: 9781934115114

;Биологические мотивации КНИГИ ;НАУКА и УЧЕБА Автор: Судаков К.В. Название: Биологические мотивации Издательство: Медицина Год: 1971 Формат: djvu Размер: 4,6 Mb +3% Для сайта: www.mirknig.comКнига посвящена описанию таких эмоциональных состояний как голод, жажда, половое возбуждение, страх. Показана роль мотивации в приспособительных реакциях организма, патология и психофармакология мотиваций.Depozit documents zero

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Extra resources for Биологические мотивации

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The outputs from the OR gates are fed into the selector unit, which selects which of these outputs are to be counted by the counter. The number of asserted lines from the selector are thus passed to the maximum detector, which in turn decides which of the subsystems, that is, which category, has the highest value. In the case of a tie, the subsystem with the lowest index is chosen. The system is evolved in two phases. First, the AND-OR subsystems are evolved separately, one at a time. All training vectors for all categories are applied to each subsystem, and fitness is measured on the outputs of the OR layer.

OR OR OR no connection connected wires ... ... AND ANDOR unit x15 primary outputs Fig. 1. PLA-based architecture Max. detector AND Counter ... Counter ... Selector primary inputs Selector C1 ANDOR unit x0 input pattern category classification Fig. 2. Increased complexity evolution architecture classifier system is then constructed by assigning a primary output to a category. Having this, the simultaneous and thus erroneous recognition of multiple hand movements is solved by selecting the category with the lowest index.

The FUR architecture gives, like the ECGP approach, good test set accuracies, and also small gaps between the accuracies for the training and test sets, indicating good generalization abilities. Further, the number of evaluations required before a high accuracy is achieved is significantly lower than for the other approaches. The use of predefined high-level building blocks selecting logical features of the inputs significantly reduces the genome size and thus the search space, in addition to making the search simpler.

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Биологические мотивации by Судаков К.В.

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