Some Local Stability Properties of an Autonomous Long Short-Term Memory Neural Network Model

Dušan M. Stipanović, Boris Murmann, Matteo Causo, Aleksandra Lekić, Vicenç Rubies Royo, Claire J. Tomlin, Edith Beigne, Sebastien Thuries, Mykhailo Zarudniev, Suzanne Lesecq

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

6 Citations (Scopus)

Abstract

In this paper some local stability results for an autonomous Long Short-Term Memory neural network model with respect to the origin are provided. In particular, it is shown through linearization that the local asymptotic stability conditions with respect to the origin only depend on one of the weight matrices. Simulations indicate that these local stability conditions greatly influence the behavior of the autonomous four-dimensional neural network in the region where each variable's values vary between minus one and one. Finally, some sufficient stability conditions for the nonlinear model are formulated as a convex program involving linear matrix inequalities.

Original languageEnglish
Title of host publication2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Volume2018-May
ISBN (Electronic)9781538648810
DOIs
Publication statusPublished - 26 Apr 2018
Externally publishedYes
Event2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Florence, Italy
Duration: 27 May 201830 May 2018

Conference

Conference2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
Country/TerritoryItaly
CityFlorence
Period27/05/1830/05/18

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