Add to ORKG[[abstract]]In this paper, a real-time approximator using a TSK-type self-evolving neural network (TSNN) is studied. The learning algorithm of the proposed TSNN not only automatically online generates and prunes the hidden neurons but also online adjusts the network parameters.[[conferencetype]]國際[[conferencedate]]20120918~20120921[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Tokyo, Japa
Single layer feedforward neural networks with hidden nodes of adaptive wavelet functions (wavenets) ...
[[abstract]]This study presents a self-organizing functional-linked neuro-fuzzy network (SFNN) for a...
This paper presents a novel method for designing an adaptive control system using radial basis funct...
[[abstract]]Though the control performances of the fuzzy neural network controller are acceptable in...
[[abstract]]This paper proposes an Elman-based self-organizing RBF neural network (ESRNN) which is a...
Online trained neural networks have become popular in recent years in the design of robust and adapt...
[[abstract]]This study proposes an indirect adaptive self-organizing RBF neural control (IASRNC) sys...
[[abstract]]Many published papers show that a TSK-type fuzzy system provides more powerful represent...
A neural network enhanced self-tuning controller is presented, which combines the attributes of neur...
The main theme of research of this project concerns the study of neutral networks to control uncerta...
[[abstract]]This paper proposes an adaptive self-organizing Hermite-polynomial-based neural control ...
[[abstract]]A TSK-type Hermite neural network (THNN) is studied in this paper. Since the output weig...
The ever increasingly tight control performance requirement of modern mechanical systems often force...
The paper investigates the possibility of using a simple approximation for evaluating the error whic...
In this paper, we presented a self-tuning control algorithm based on a three layers perceptron type ...
Single layer feedforward neural networks with hidden nodes of adaptive wavelet functions (wavenets) ...
[[abstract]]This study presents a self-organizing functional-linked neuro-fuzzy network (SFNN) for a...
This paper presents a novel method for designing an adaptive control system using radial basis funct...
[[abstract]]Though the control performances of the fuzzy neural network controller are acceptable in...
[[abstract]]This paper proposes an Elman-based self-organizing RBF neural network (ESRNN) which is a...
Online trained neural networks have become popular in recent years in the design of robust and adapt...
[[abstract]]This study proposes an indirect adaptive self-organizing RBF neural control (IASRNC) sys...
[[abstract]]Many published papers show that a TSK-type fuzzy system provides more powerful represent...
A neural network enhanced self-tuning controller is presented, which combines the attributes of neur...
The main theme of research of this project concerns the study of neutral networks to control uncerta...
[[abstract]]This paper proposes an adaptive self-organizing Hermite-polynomial-based neural control ...
[[abstract]]A TSK-type Hermite neural network (THNN) is studied in this paper. Since the output weig...
The ever increasingly tight control performance requirement of modern mechanical systems often force...
The paper investigates the possibility of using a simple approximation for evaluating the error whic...
In this paper, we presented a self-tuning control algorithm based on a three layers perceptron type ...
Single layer feedforward neural networks with hidden nodes of adaptive wavelet functions (wavenets) ...
[[abstract]]This study presents a self-organizing functional-linked neuro-fuzzy network (SFNN) for a...
This paper presents a novel method for designing an adaptive control system using radial basis funct...