Asymptotical stability for fractional‐order Hopfield neural networks with multiple time delays

Neural networks for/in biological studies, artificial life and related topics (92B20) Stability theory of functional-differential equations (34K20) Functional-differential equations with fractional derivatives (34K37)

Cites Work

Unnamed Item
Analytical and numerical methods for the stability analysis of linear fractional delay differential equations
Stability analysis of fractional-order complex-valued neural networks with time delays
The Grünwald-Letnikov method for fractional differential equations
Asymptotic stability of linear fractional systems with constant coefficients and small time-dependent perturbations
Dissipativity and stability analysis for fractional functional differential equations
Memory pattern analysis of cellular neural networks
Razumikhin-type stability theorems for functional fractional-order differential systems and applications
Fractional differential equations with a constant delay: stability and asymptotics of solutions
Order stars and stability for delay differential equations
A stability criterion for fractional-order complex-valued differential equations with distributed delays
Robust generalized Mittag-Leffler synchronization of fractional order neural networks with discontinuous activation and impulses
Stability regions for fractional differential systems with a time delay
On asymptotic properties of solutions to fractional differential equations
Lyapunov stability theorem about fractional system without and with delay
Global Attractivity in Delayed Hopfield Neural Network Models
Lattice fractional diffusion equation of random order
New conditions for global stability of neural networks with application to linear and quadratic programming problems
Exponential and fixed‐time stabilization of memristive neural networks with mixed delays
Mittag‐Leffler stability and adaptive impulsive synchronization of fractional order neural networks in quaternion field
Neural networks and physical systems with emergent collective computational abilities.
Neurons with graded response have collective computational properties like those of two-state neurons.

This page was built for publication: Asymptotical stability for fractional‐order Hopfield neural networks with multiple time delays