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Устойчивость многослойных рекурсивных нейронных сетей

Устойчивость многослойных рекурсивных нейронных сетей

Abstract

Получены численные критерии устойчивости многослойных дискретных нейронных сетей. Построены области устойчивости в пространстве параметров для таких сетей. Задача сводится к проблеме устойчивости матричных разностных уравнений высоких порядков с запаздыванием. Основным средством решения проблемы являются конусы устойчивости.

Numerical stability criteria are described for multilayer discrete-time neural networks. Stability domains in the space of parameters are built. The problem reduces to the stability problem for difference matrix equations of a higher order with delay. Stability cones are major tolls for problem solution.

Keywords

НЕЙРОННЫЕ СЕТИ, РАЗНОСТНЫЕ МАТРИЧНЫЕ УРАВНЕНИЯ, УСТОЙЧИВОСТЬ РАЗНОСТНЫХ УРАВНЕНИЙ, МНОГОСЛОЙНЫЕ СЕТИ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold