Title :
An adaptive higher-order neural networks (AHONN) and its approximation capabilities
Author :
Xu, Shuxiang ; Zhang, Ming
Author_Institution :
Sch. of Comput., Tasmania Univ., Hobart, Tas., Australia
Abstract :
The approximation capabilities of an adaptive higher-order neural network (AHONN) with a neuron-adaptive activation function (NAF) to any nonlinear continuous functional and any nonlinear continuous operator are studied. Universal approximation theorems of AHONN to continuous functionals and continuous operators are given, and learning algorithms are derived to tune the free parameters in NAF as well as connection weights between neurons. We apply the algorithms to approximate continuous dynamical systems (operators).
Keywords :
adaptive systems; function approximation; learning (artificial intelligence); neural nets; AHONN; adaptive higher-order neural networks; approximation capabilities; connection weights; continuous dynamical systems; free parameters; learning algorithms; neuron-adaptive activation function; nonlinear continuous functional operator; universal approximation theorems; Adaptive systems; Approximation algorithms; Australia; Computer architecture; Computer networks; Electronic mail; Feedforward neural networks; Function approximation; Neural networks; Neurons;
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
DOI :
10.1109/ICONIP.2002.1198179
