In this manuscript, we principally probe into a class of fractional-order tri-neuron neural networks incorporating delays. Making use of fixed point theorem, we prove the existence and uniqueness of solution to the fractional-order tri-neuron neural networks incorporating delays. By virtue of a suitable function, we prove the uniformly boundedness of the solution to the fractional-order tri-neuron neural networks incorporating delays. With the aid of the stability theory and bifurcation knowledge of fractional-order differential equation, a new delay-independent condition to guarantee the stability and creation of Hopf bifurcation of the fractional-order tri-neuron neural networks incorporating delays is established. Taking advantage of the...
In this paper, we study the synchronization of a new fractional-order neural network with multiple d...
This paper investigates a neural network modeled by a scalar delay differential equation. The focus ...
At the beginning, a class of fractional-order delayed neural networks were employed. It is known tha...
This work is chiefly concerned with the stability behavior and the appearance of Hopf bifurcation of...
In this current study, we formulate a kind of new fractional BAM neural network model concerning fiv...
Abstract This paper considers a class of fractional-order complex-valued Hopfield neural networks (C...
AbstractA neural network model with three neurons and a single time delay is considered. Its linear ...
In this paper, we address the problem of bifurcation control for a delayed neuron system. By introdu...
Dynamics of discrete‐time neural networks have not been well documented yet in fractional‐order case...
This Master thesis consists of four chapters, mainly considering the stability and bifurcation in th...
In the present study, we deal with the stability and the onset of Hopf bifurcation of two type delay...
At present, the theory and application of fractional-order neural networks remain in the exploratory...
The lack of a conventional Lyapunov theory for fractional-order (FO) systems makes it difficult to s...
© 2016, Springer International Publishing. In this paper, we study a class of fractional-order cellu...
This article investigates quasi-synchronization for a class of fractional-order delayed neural netwo...
In this paper, we study the synchronization of a new fractional-order neural network with multiple d...
This paper investigates a neural network modeled by a scalar delay differential equation. The focus ...
At the beginning, a class of fractional-order delayed neural networks were employed. It is known tha...
This work is chiefly concerned with the stability behavior and the appearance of Hopf bifurcation of...
In this current study, we formulate a kind of new fractional BAM neural network model concerning fiv...
Abstract This paper considers a class of fractional-order complex-valued Hopfield neural networks (C...
AbstractA neural network model with three neurons and a single time delay is considered. Its linear ...
In this paper, we address the problem of bifurcation control for a delayed neuron system. By introdu...
Dynamics of discrete‐time neural networks have not been well documented yet in fractional‐order case...
This Master thesis consists of four chapters, mainly considering the stability and bifurcation in th...
In the present study, we deal with the stability and the onset of Hopf bifurcation of two type delay...
At present, the theory and application of fractional-order neural networks remain in the exploratory...
The lack of a conventional Lyapunov theory for fractional-order (FO) systems makes it difficult to s...
© 2016, Springer International Publishing. In this paper, we study a class of fractional-order cellu...
This article investigates quasi-synchronization for a class of fractional-order delayed neural netwo...
In this paper, we study the synchronization of a new fractional-order neural network with multiple d...
This paper investigates a neural network modeled by a scalar delay differential equation. The focus ...
At the beginning, a class of fractional-order delayed neural networks were employed. It is known tha...