The use of n-tuple or weightless neural networks as pattern recognition devices has been well documented. They have a significant advantages over more common networks paradigms, such as the multilayer perceptron in that they can be easily implemented in digital hardware using standard random access memories. To date, n-tuple networks have predominantly been used as fast pattern classification devices. The paper describes how n-tuple techniques can be used in the hardware implementation of a general auto-associative network
Rückert U. An Associative Memory with Neural Architecture and its VLSI Implementation. In: Milutinov...
Multi-dimensional classification tasks by neural methods are interesting for their performances and ...
Abstract. Random Access Memory (RAM) nodes can play the role of artificial neurons that are addresse...
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...
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 idea of n-tuple sampling as a basis for pattern recognition, as proposed by Bledsoe and Browning...
The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from ...
The design of an auto-associative memory based on a spiking neural network is described. Delays rath...
The N-tuple approximation network offers many advantages over conventional neural networks in terms ...
A new efficient learning algorithm of associative memory neural network is proposed, with the follow...
N-tuple neural networks (NTNNs) have been successfully applied to both pattern recognition and funct...
We propose a new associative memory to improve its noise tolerance and storage capacity. Our underly...
A novel form of self-organising neural network, based on the N-tuple sampling of binary patterns, is...
Rückert U. An Associative Memory with Neural Architecture and its VLSI Implementation. In: Milutinov...
Multi-dimensional classification tasks by neural methods are interesting for their performances and ...
Abstract. Random Access Memory (RAM) nodes can play the role of artificial neurons that are addresse...
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...
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 idea of n-tuple sampling as a basis for pattern recognition, as proposed by Bledsoe and Browning...
The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from ...
The design of an auto-associative memory based on a spiking neural network is described. Delays rath...
The N-tuple approximation network offers many advantages over conventional neural networks in terms ...
A new efficient learning algorithm of associative memory neural network is proposed, with the follow...
N-tuple neural networks (NTNNs) have been successfully applied to both pattern recognition and funct...
We propose a new associative memory to improve its noise tolerance and storage capacity. Our underly...
A novel form of self-organising neural network, based on the N-tuple sampling of binary patterns, is...
Rückert U. An Associative Memory with Neural Architecture and its VLSI Implementation. In: Milutinov...
Multi-dimensional classification tasks by neural methods are interesting for their performances and ...
Abstract. Random Access Memory (RAM) nodes can play the role of artificial neurons that are addresse...