Huizhen Yan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Huizhen Yan has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Bo Li
School of Information Science and Engineering, Dalian Polytechnic University, Dalian, China
1 shared publication - Jun Mou
Dalian Polytechnic University
1 shared publication - Santo Banerjee
Department of Mathematical Sciences, Giuseppe Luigi Lagrange, Politecnico di Torino, Torino, Italy
1 shared publication - Tao Ma
School of Information Science and Engineering, Dalian Polytechnic University, Dalian 116034, China
1 shared publication
Latest Publications
- Open Access
- 1 November 2022
- Published by MDPI AG in Fractal and Fractional
- Vol. 6 (11) , 637
Study on the Complex Dynamical Behavior of the Fractional-Order Hopfield Neural Network System and Its Implementation
The complex dynamics analysis of fractional-order neural networks is a cutting-edge topic in the field of neural network research. In this paper, a fractional-order Hopfield neural network (FOHNN) system is proposed, which contains four neurons. Using the Adomian decomposition method, the FOHNN system is solved. The dissipative characteristics of the system are discussed, as well as the equilibrium point is resolved. The characteristics of the dynamics through the phase diagram, the bifurcation diagram, the Lyapunov exponential spectrum, and the Lyapunov dimension of the system are investigated. The circuit of the system was also designed, based on the Multisim simulation platform, and the simulation of the circuit was realized. The simulation results show that the proposed FOHNN system exhibits many interesting phenomena, which provides more basis for the study of complex brain working patterns, and more references for the design, as well as the hardware implementation of the realized fractional-order neural network circuit.
- 1 November 2022
- Published by MDPI AG in Fractal and Fractional
- Vol. 6 (11) , 637
Open AccessStudy on the Complex Dynamical Behavior of the Fractional-Order Hopfield Neural Network System and Its Implementation
The complex dynamics analysis of fractional-order neural networks is a cutting-edge topic in the field of neural network research. In this paper, a fractional-order Hopfield neural network (FOHNN) system is proposed, which contains four neurons. Using the Adomian decomposition method, the FOHNN system is solved. The dissipative characteristics of the system are discussed, as well as the equilibrium point is resolved. The characteristics of the dynamics through the phase diagram, the bifurcation diagram, the Lyapunov exponential spectrum, and the Lyapunov dimension of the system are investigated. The circuit of the system was also designed, based on the Multisim simulation platform, and the simulation of the circuit was realized. The simulation results show that the proposed FOHNN system exhibits many interesting phenomena, which provides more basis for the study of complex brain working patterns, and more references for the design, as well as the hardware implementation of the realized fractional-order neural network circuit.