Add to ORKG[[abstract]]This paper deals with the problem of state estimation for discrete-time recurrent neural networks with interval timevarying delay. The activation functions are assumed to be globally Lipschitz continuous. A delay-range-dependent condition for the existence of state estimators is proposed. Via available output measurements and solutions to certain linear matrix inequalities, general full-order state estimators are designed that ensure globally asymptotic stability. Two illustrative examples are given to demonstrate the effectiveness and applicability
This paper examines a passivity analysis for a class of discrete-time recurrent neural networks (DRN...
[[abstract]]This paper examines a passivity analysis for a class of discrete-time recurrent neural n...
[[abstract]]This paper examines a passivity analysis for a class of discrete-time recurrent neural n...
[[abstract]]The state estimation problem for discrete-time recurrent neural networks with both inter...
[[abstract]]The state estimation problem for discrete-time recurrent neural networks with both inter...
[[abstract]]This paper deals with the problem of state estimation for discrete stochastic recurrent ...
[[abstract]]This paper deals with the problem of state estimation for discrete stochastic recurrent ...
This article deals with the problem of delay-dependent state estimation for discrete-time neural net...
[[abstract]]The current paper performs a global robust stability analysis for a class of discrete-ti...
[[abstract]]This paper deals with the problem of delay-dependent robust H ∞ control for discrete-tim...
Abstract: This paper establishes new delay-range-dependent, robust global stability for a class of d...
[[abstract]]This paper considers the problem of global robust delay-range-dependent stability for un...
The state estimation problem is discussed for discrete Markovian jump\ud neural networks with time-v...
This paper is concerned with the state estimation problem for a class of Markovian neural networks w...
A delay-dependent state estimation problem for a class of neural networks with time-varying delays i...
This paper examines a passivity analysis for a class of discrete-time recurrent neural networks (DRN...
[[abstract]]This paper examines a passivity analysis for a class of discrete-time recurrent neural n...
[[abstract]]This paper examines a passivity analysis for a class of discrete-time recurrent neural n...
[[abstract]]The state estimation problem for discrete-time recurrent neural networks with both inter...
[[abstract]]The state estimation problem for discrete-time recurrent neural networks with both inter...
[[abstract]]This paper deals with the problem of state estimation for discrete stochastic recurrent ...
[[abstract]]This paper deals with the problem of state estimation for discrete stochastic recurrent ...
This article deals with the problem of delay-dependent state estimation for discrete-time neural net...
[[abstract]]The current paper performs a global robust stability analysis for a class of discrete-ti...
[[abstract]]This paper deals with the problem of delay-dependent robust H ∞ control for discrete-tim...
Abstract: This paper establishes new delay-range-dependent, robust global stability for a class of d...
[[abstract]]This paper considers the problem of global robust delay-range-dependent stability for un...
The state estimation problem is discussed for discrete Markovian jump\ud neural networks with time-v...
This paper is concerned with the state estimation problem for a class of Markovian neural networks w...
A delay-dependent state estimation problem for a class of neural networks with time-varying delays i...
This paper examines a passivity analysis for a class of discrete-time recurrent neural networks (DRN...
[[abstract]]This paper examines a passivity analysis for a class of discrete-time recurrent neural n...
[[abstract]]This paper examines a passivity analysis for a class of discrete-time recurrent neural n...