This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the KMeans clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the w...
This thesis provides a bridge between analytical modeling and neural network modeling. Two different...
This paper extends the sequential learning algorithm strategy of two different types of adaptive ra...
This paper presents a modified RBF network with additional linear input connections together with a ...
This paper uses the radial basis function neural network (RBFNN) for system identification of nonli...
A look is taken at the use of radial basis functions (RBFs), for nonlinear system identification. RB...
Abstract. One of the key problem in system identification is finding a suitable model structure. In ...
This paper investigates the identification of discrete-time non-linear systems using radial basis fu...
In many physical systems, it is difficult to obtain a model structure that is highly nonlinear and c...
Proceedings of the International Joint Conference on Neural Networks21833-183685OF
This paper presents an artificial intelligence application using a nonconventional mathematical tool...
The identification of nonlinear dynamical systems is of great importance in many areas of engineeri...
The paper focuses on the application of artificial neural networks (ANN) for modelling of nonlinear ...
Abstract—A continuous forward algorithm (CFA) is proposed for nonlinear modelling and identification...
This paper presents a modified RBF network with additional linear input connections together with a ...
Abstract: In this study, identification of a nonlinear function will be presented by neural network ...
This thesis provides a bridge between analytical modeling and neural network modeling. Two different...
This paper extends the sequential learning algorithm strategy of two different types of adaptive ra...
This paper presents a modified RBF network with additional linear input connections together with a ...
This paper uses the radial basis function neural network (RBFNN) for system identification of nonli...
A look is taken at the use of radial basis functions (RBFs), for nonlinear system identification. RB...
Abstract. One of the key problem in system identification is finding a suitable model structure. In ...
This paper investigates the identification of discrete-time non-linear systems using radial basis fu...
In many physical systems, it is difficult to obtain a model structure that is highly nonlinear and c...
Proceedings of the International Joint Conference on Neural Networks21833-183685OF
This paper presents an artificial intelligence application using a nonconventional mathematical tool...
The identification of nonlinear dynamical systems is of great importance in many areas of engineeri...
The paper focuses on the application of artificial neural networks (ANN) for modelling of nonlinear ...
Abstract—A continuous forward algorithm (CFA) is proposed for nonlinear modelling and identification...
This paper presents a modified RBF network with additional linear input connections together with a ...
Abstract: In this study, identification of a nonlinear function will be presented by neural network ...
This thesis provides a bridge between analytical modeling and neural network modeling. Two different...
This paper extends the sequential learning algorithm strategy of two different types of adaptive ra...
This paper presents a modified RBF network with additional linear input connections together with a ...