The aim of this chapter is to introduce background concepts in nonlinear systems identification and control with artificial neural networks. As this chapter is just an overview, with a limited page space, only the basic ideas will be explained here. The reader is encouraged, for a more detailed explanation of a specific topic of interest, to consult the references given throughout the text. Additionally, as general books in the field of neural networks, the books by Haykin [1] and Principe et al. [2] are suggested. Regarding nonlinear systems identification, covering both classical and neural and neuro-fuzzy methodologies, Reference 3 is recommended. References 4 and 5 should be used in the context of B-spline networks
AbstractModels for the identification and control of nonlinear dynamical systems using neural networ...
Most industrial systems are nonlinear. In these applications the conventional identification and con...
This paper uses the radial basis function neural network (RBFNN) for system identification of nonli...
The aim of this chapter is to introduce background concepts in nonlinear systems identification and...
This paper presents a first attempt to relate the experimental studies to theoretical developments a...
The series Advances in Industrial Control aims to report and encourage technology transfer in contro...
This paper presents a discussion of the applicability of neural networks in the identification and c...
In this report some examples on system identification of non-linear systems with neural networks are...
In this report some examples on system identification of non-linear systems with neural networks are...
In this report some examples on system identification of non-linear systems with neural networks are...
The paper summarizes some results of nonlinear system modelling and identification. Connectionswith ...
This book provides engineers and scientists in academia and industry with a thorough understanding o...
As an imitation of the biological nervous systems, neural networks (NNs), which have been characteri...
Lately, there has been an extensive interest in the possible uses of neural networks for nonlinear s...
Most industrial systems are nonlinear. In these applications the conventional identification and con...
AbstractModels for the identification and control of nonlinear dynamical systems using neural networ...
Most industrial systems are nonlinear. In these applications the conventional identification and con...
This paper uses the radial basis function neural network (RBFNN) for system identification of nonli...
The aim of this chapter is to introduce background concepts in nonlinear systems identification and...
This paper presents a first attempt to relate the experimental studies to theoretical developments a...
The series Advances in Industrial Control aims to report and encourage technology transfer in contro...
This paper presents a discussion of the applicability of neural networks in the identification and c...
In this report some examples on system identification of non-linear systems with neural networks are...
In this report some examples on system identification of non-linear systems with neural networks are...
In this report some examples on system identification of non-linear systems with neural networks are...
The paper summarizes some results of nonlinear system modelling and identification. Connectionswith ...
This book provides engineers and scientists in academia and industry with a thorough understanding o...
As an imitation of the biological nervous systems, neural networks (NNs), which have been characteri...
Lately, there has been an extensive interest in the possible uses of neural networks for nonlinear s...
Most industrial systems are nonlinear. In these applications the conventional identification and con...
AbstractModels for the identification and control of nonlinear dynamical systems using neural networ...
Most industrial systems are nonlinear. In these applications the conventional identification and con...
This paper uses the radial basis function neural network (RBFNN) for system identification of nonli...