Strongly Unpredictable Oscillations of Hopfield-Type Neural Networks

In this paper, unpredictable oscillations in Hopfield-type neural networks is under investigation. The motion strongly relates to Poincaré chaos. Thus, the importance of the dynamics is indisputable for those problems of artificial intelligence, brain activity and robotics, which rely on chaos. Suff...

Full description

Bibliographic Details
Main Authors: Marat Akhmet, Madina Tleubergenova, Zakhira Nugayeva
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/8/10/1791
Description
Summary:In this paper, unpredictable oscillations in Hopfield-type neural networks is under investigation. The motion strongly relates to Poincaré chaos. Thus, the importance of the dynamics is indisputable for those problems of artificial intelligence, brain activity and robotics, which rely on chaos. Sufficient conditions for the existence and uniqueness of exponentially stable unpredictable solutions are determined. The oscillations continue the line of periodic and almost periodic motions, which already are verified as effective instruments of analysis and applications for image recognition, information processing and other areas of neuroscience. The concept of strongly unpredictable oscillations is a significant novelty of the present research, since the presence of chaos in each coordinate of the space state provides new opportunities in applications. Additionally to the theoretical analysis, we have provided strong simulation arguments, considering that all of the assumed conditions are fulfilled.
ISSN:2227-7390