The idea of n-tuple sampling as a basis for pattern recognition, as proposed by Bledsoe and Browning (1959), remains a viable approach to a range of pattern classification tasks especially where speed of learning is of importance. The formal relationship between n-tuple neural networks and more mainstream network paradigms, such as radial basis function networks, and classical nonparametric pattern classifiers, such as kernel estimation, is considered, and it is described how the classic n-tuple recogniser and the n-tuple regression network form differing approximations in the classification proces
This thesis brings together two strands of neural networks research - weightless systems and statis...
The Scanning N-Tuple classifier (SNT) is a fast and accurate method for classifying sequences. Appli...
This paper concentrates on the swarm intelligence based bio-inspired approach to optimize N-tuple cl...
The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from ...
The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from ...
N-tuple neural networks (NTNNs) have been successfully applied to both pattern recognition and funct...
The use of n-tuple or weightless neural networks as pattern recognition devices i well known (Aleksa...
The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from ...
The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleks...
The use of n-tuple or weightless neural networks as pattern recognition devices has been well docume...
A new method of applying n-tuple recognition techniques to handwritten OCR has recently been reporte...
An N-tuple Neural Network (NNN) is described in which each node fires selectively to its own table o...
Abstract—The anticipated behavior of the n-tuple classification system is that it gives the highest ...
A novel form of self-organising neural network, based on the N-tuple sampling of binary patterns, is...
One family of classifiers which lias has considerable experimental success over the last thirty year...
This thesis brings together two strands of neural networks research - weightless systems and statis...
The Scanning N-Tuple classifier (SNT) is a fast and accurate method for classifying sequences. Appli...
This paper concentrates on the swarm intelligence based bio-inspired approach to optimize N-tuple cl...
The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from ...
The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from ...
N-tuple neural networks (NTNNs) have been successfully applied to both pattern recognition and funct...
The use of n-tuple or weightless neural networks as pattern recognition devices i well known (Aleksa...
The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from ...
The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleks...
The use of n-tuple or weightless neural networks as pattern recognition devices has been well docume...
A new method of applying n-tuple recognition techniques to handwritten OCR has recently been reporte...
An N-tuple Neural Network (NNN) is described in which each node fires selectively to its own table o...
Abstract—The anticipated behavior of the n-tuple classification system is that it gives the highest ...
A novel form of self-organising neural network, based on the N-tuple sampling of binary patterns, is...
One family of classifiers which lias has considerable experimental success over the last thirty year...
This thesis brings together two strands of neural networks research - weightless systems and statis...
The Scanning N-Tuple classifier (SNT) is a fast and accurate method for classifying sequences. Appli...
This paper concentrates on the swarm intelligence based bio-inspired approach to optimize N-tuple cl...