Dynamic Analysis and Implementation of FPGA for a New 4D Fractional-Order Memristive Hopfield Neural Network

Fractal and Fractional, Journal Year: 2025, Volume and Issue: 9(2), P. 115 - 115

Published: Feb. 13, 2025

Memristor-based fractional-order chaotic systems can record information from the past, present, and future, describe real world more accurately than integer-order systems. This paper proposes a novel memristor model verifies its characteristics through pinched loop (PHL) method. Subsequently, new memristive Hopfield neural network (4D-FOMHNN) is introduced to simulate induced current, accompanied by Caputo’s definition of fractional order. An Adomian decomposition method (ADM) employed for system solution. By varying parameters order 4D-FOMHNN, rich dynamic behaviors including transient chaos, coexistence attractors are observed using methods such as bifurcation diagrams Lyapunov exponent analysis. Finally, proposed FOMHNN implemented on field-programmable gate array (FPGA), oscilloscope observation results consistent with MATLAB numerical simulation results, which further validate theoretical analysis provide basis application in field encryption.

Language: Английский

Synchronization in Scale-Free Neural Networks with Heterogeneous Time Delay

Integration, Journal Year: 2025, Volume and Issue: unknown, P. 102387 - 102387

Published: Feb. 1, 2025

Language: Английский

Memristive multi-wing chaotic hopfield neural network for LiDAR data security

Nonlinear Dynamics, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 20, 2025

Language: Английский