Finite-Time Projective Synchronization in Fractional-Order Inertial Memristive Neural Networks: A Novel Approach to Image Encryption
Year: 2024
Type: article
Abstract: This paper presents a novel finite-time projective synchronization (FTPS) control strategy for fractional-order inertial memristive neural networks (FOIMNNs), exploring its application in image encryption. A sufficient condition for ensuring FTPS in FOIMNNs is established and validated through numerical simulations. These simulations indicate that the proposed strategy provides reliable synchronization performance. Furthermore, an efficient method for image encryption was developed, potentially improving data security. Comparative analyses with existing methods suggest that this approach could offer incremental benefits in secure communication and data protection.
Source: Fractal and Fractional
Authors: Huixian Weng, Yongqing Yang, Rixu Hao, Fengyi Liu
Institutions: Jiangnan University, Wuxi University
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,069
OpenAlex ID: W4403749766