Dynamics of $$\mu $$-piecewise pseudo almost periodic solutions of neutral-type inertial neural networks models: existence and attractiveness

Autor:	Khalil Ezzinbi, Fritz Mbounja Béssémè
Rok vydání:	2021
Předmět:	Inertial frame of reference Artificial neural network Exponential stability Differential equation Cognitive Neuroscience Mathematical analysis Piecewise Uniqueness Type (model theory) Research Article Mathematics Exponential function
Zdroj:	Cogn Neurodyn
ISSN:	1871-4099 1871-4080
DOI:	10.1007/s11571-021-09707-9
Popis:	In this work, we use measure theory to provide new sufficient conditions for the existence, uniqueness and global exponential stability of piecewise pseudo almost periodic solutions of neutral-type inertial neural networks with mixed delay and impulsive perturbations. By proposing a variable substitution, the neutral-type inertial neural networks can be rewritten as a first-order differential equation. As a consequence, we investigate the exponential attractiveness of $$\mu $$ -piecewise pseudo almost periodic solutions of the considered model. Moreover, some numerical simulations are given to illustrate our main results.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31d2e2ad28a1c006fc8becb0b9c83aa3 https://doi.org/10.1007/s11571-021-09707-9 Zobrazit plný text záznamu Full text from SpringerLink