Nonlinear system theory ideas have led to a method for approximating the dynamics of a nonlinear system in a bounded region of its state space, by training a feedforward neural network which is then reconfigured in recursive mode to provide a stand-alone simulator of the system. The input layer of the neural network contains time-delayed samples of one or more system outputs and control inputs. Autonomous systems can be simulated in this way by providing impulse inputs
A nonaffine discrete-time system represented by the nonlinear autoregressive moving average with eXo...
This article aims at proposing an adaptive neural control strategy for a class of nonlinear time-del...
This article aims at proposing an adaptive neural control strategy for a class of nonlinear time-del...
Nonlinear system theory ideas have led to a method for approximating the dynamics of a non-linear sy...
AbstractModels for the identification and control of nonlinear dynamical systems using neural networ...
Artificial neural networks have been employed for rapid and efficient dynamics and control analysis ...
In this research, a comparative study of two recurrent neural networks, nonlinear autoregressive wit...
This paper presents a discussion of the applicability of neural networks in the identification and c...
This paper discusses memory neuron networks as models for identification and adaptive control of non...
This paper discusses memory neuron networks as models for identification and adaptive control of non...
dentification and control of nonlinear dynamic systems are typically established on a case-by-case b...
dentification and control of nonlinear dynamic systems are typically established on a case-by-case b...
The authors describe a special type of dynamic neural network called the recursive neural network (R...
This study considers the problem of using approximate way for realizing the neural supervi...
This study considers the problem of using approximate way for realizing the neural supervi...
A nonaffine discrete-time system represented by the nonlinear autoregressive moving average with eXo...
This article aims at proposing an adaptive neural control strategy for a class of nonlinear time-del...
This article aims at proposing an adaptive neural control strategy for a class of nonlinear time-del...
Nonlinear system theory ideas have led to a method for approximating the dynamics of a non-linear sy...
AbstractModels for the identification and control of nonlinear dynamical systems using neural networ...
Artificial neural networks have been employed for rapid and efficient dynamics and control analysis ...
In this research, a comparative study of two recurrent neural networks, nonlinear autoregressive wit...
This paper presents a discussion of the applicability of neural networks in the identification and c...
This paper discusses memory neuron networks as models for identification and adaptive control of non...
This paper discusses memory neuron networks as models for identification and adaptive control of non...
dentification and control of nonlinear dynamic systems are typically established on a case-by-case b...
dentification and control of nonlinear dynamic systems are typically established on a case-by-case b...
The authors describe a special type of dynamic neural network called the recursive neural network (R...
This study considers the problem of using approximate way for realizing the neural supervi...
This study considers the problem of using approximate way for realizing the neural supervi...
A nonaffine discrete-time system represented by the nonlinear autoregressive moving average with eXo...
This article aims at proposing an adaptive neural control strategy for a class of nonlinear time-del...
This article aims at proposing an adaptive neural control strategy for a class of nonlinear time-del...