Add to ORKGWe present a new type of constructive algorithm for incremental learning. The algorithm overcomes many of the problems associated with standard back propagation such as speed and optimum network size. We investigate the ability of the network to learn and test the resulting generalisation of the network
AbstractArtificial neural network (ANN) has wide applications such as data processing and classifica...
This paper investigates incremental multiagent learning in structured networks. Learning examples ar...
We propose a new incremental learning method of Self-Organizing Map. There are three problems in the...
Abstract—We develop, in this brief, a new constructive learning algorithm for feedforward neural net...
Abstract-How to learn new knowledge without forgetting old knowledge is a key issue in designing an ...
[[abstract]]How to learn new knowledge without forgetting old knowledge is a key issue in designing ...
A classi er for discrete-valued variable classi cation problems is presented. The system utilizes an...
We present a new incremental procedure for supervised learning with noisy data. Each step consists i...
An incremental, higher-order, non-recurrent network combines two properties found to be useful for l...
AbstractThe present paper deals with a systematic study of incremental learning algorithms. The gene...
Methods to speed up learning in back propagation and to optimize the network architecture have been ...
M.Ing. (Electrical And Electronic Engineering)This dissertation describes the development of a syste...
There are been a resurgence of interest in the neural networks field in recent years, provoked in pa...
In this paper, a new hybrid incremental learning algorithm for Bayesian network structures is propos...
This paper presents a constructive neural network with sigmoidal units and multiplication units, whi...
AbstractArtificial neural network (ANN) has wide applications such as data processing and classifica...
This paper investigates incremental multiagent learning in structured networks. Learning examples ar...
We propose a new incremental learning method of Self-Organizing Map. There are three problems in the...
Abstract—We develop, in this brief, a new constructive learning algorithm for feedforward neural net...
Abstract-How to learn new knowledge without forgetting old knowledge is a key issue in designing an ...
[[abstract]]How to learn new knowledge without forgetting old knowledge is a key issue in designing ...
A classi er for discrete-valued variable classi cation problems is presented. The system utilizes an...
We present a new incremental procedure for supervised learning with noisy data. Each step consists i...
An incremental, higher-order, non-recurrent network combines two properties found to be useful for l...
AbstractThe present paper deals with a systematic study of incremental learning algorithms. The gene...
Methods to speed up learning in back propagation and to optimize the network architecture have been ...
M.Ing. (Electrical And Electronic Engineering)This dissertation describes the development of a syste...
There are been a resurgence of interest in the neural networks field in recent years, provoked in pa...
In this paper, a new hybrid incremental learning algorithm for Bayesian network structures is propos...
This paper presents a constructive neural network with sigmoidal units and multiplication units, whi...
AbstractArtificial neural network (ANN) has wide applications such as data processing and classifica...
This paper investigates incremental multiagent learning in structured networks. Learning examples ar...
We propose a new incremental learning method of Self-Organizing Map. There are three problems in the...