The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from the European Community StatLog project, so that the results could be compared with those reported for the 23 other algorithms the project tested. The results indicate that this ultra-fast memory-based method is a viable competitor with the others, which include optimisation-based neural network algorithms, even though the theory of memory-based neural computing is less highly developed in terms of statistical theory
We present results concerning the application of the Good-Turing (GT) estimation method to the frequ...
An N-tuple Neural Network (NNN) is described in which each node fires selectively to its own table o...
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 ...
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 i well known (Aleksa...
This thesis brings together two strands of neural networks research - weightless systems and statis...
The idea of n-tuple sampling as a basis for pattern recognition, as proposed by Bledsoe and Browning...
One family of classifiers which lias has considerable experimental success over the last thirty year...
The subject of this thesis is the n-tuple net.work (RAMnet). The major advantage of RAMnets is their...
The use of n-tuple or weightless neural networks as pattern recognition devices has been well docume...
Abstract—The anticipated behavior of the n-tuple classification system is that it gives the highest ...
A new method of applying n-tuple recognition techniques to handwritten OCR has recently been reporte...
Among numerous pattern recognition methods the neural network approach has been the subject of much ...
We present results concerning the application of the Good-Turing (GT) estimation method to the frequ...
An N-tuple Neural Network (NNN) is described in which each node fires selectively to its own table o...
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 ...
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 i well known (Aleksa...
This thesis brings together two strands of neural networks research - weightless systems and statis...
The idea of n-tuple sampling as a basis for pattern recognition, as proposed by Bledsoe and Browning...
One family of classifiers which lias has considerable experimental success over the last thirty year...
The subject of this thesis is the n-tuple net.work (RAMnet). The major advantage of RAMnets is their...
The use of n-tuple or weightless neural networks as pattern recognition devices has been well docume...
Abstract—The anticipated behavior of the n-tuple classification system is that it gives the highest ...
A new method of applying n-tuple recognition techniques to handwritten OCR has recently been reporte...
Among numerous pattern recognition methods the neural network approach has been the subject of much ...
We present results concerning the application of the Good-Turing (GT) estimation method to the frequ...
An N-tuple Neural Network (NNN) is described in which each node fires selectively to its own table o...
This paper concentrates on the swarm intelligence based bio-inspired approach to optimize N-tuple cl...