Open AccessExistence and global exponential stability of compact almost automorphic solutions for Clifford-valued high-order Hopfield neutral neural networks with $ D $ operator
Author(s) -
Yuwei Cao,
AUTHOR_ID,
Bing Li
Publication year - 2022
Publication title -
aims mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 15
ISSN - 2473-6988
DOI - 10.3934/math.2022344
Subject(s) - mathematics , uniqueness , artificial neural network , class (philosophy) , exponential stability , pure mathematics , order (exchange) , stability (learning theory) , fixed point theorem , operator (biology) , exponential function , discrete mathematics , mathematical analysis , computer science , physics , biochemistry , chemistry , finance , repressor , nonlinear system , quantum mechanics , artificial intelligence , machine learning , transcription factor , economics , gene
In this paper, a class of Clifford-valued higher-order Hopfield neural networks with $ D $ operator is studied by non-decomposition method. Except for time delays, all parameters, activation functions and external inputs of this class of neural networks are Clifford-valued functions. Based on Banach fixed point theorem and differential inequality technique, we obtain the existence, uniqueness and global exponential stability of compact almost automorphic solutions for this class of neural networks. Our results of this paper are new. In addition, two examples and their numerical simulations are given to illustrate our results.