Add to ORKGAbstract. Random Access Memory (RAM) nodes can play the role of artificial neurons that are addressed by Boolean inputs and produce Boolean outputs. The weightless neural network (WNN) approach has an implicit inspiration in the decoding process observed in the dendritic trees of biological neurons. An overview on recent advances in weightless neural systems is presented here. Theoretical aspects, such as the VC dimension of WNNs, architectural extensions, such as the Bleaching mechanism, and novel quantum WNN models, are discussed. A set of recent successful applications and cognitive explorations are also summarized here. 1 From n-tuples to artificial consciousness It has been 55 years since Bledsoe and Browning [20] introduced the n-tupl...
Artificial neural net (ANN) models, or neural networks, connectionist models, parallel distributed p...
Artificial Neural Networks (ANNs) have been developed in an attempt to emulate the information proce...
Weightless neural networks (WNNs) are an alternative pattern recognition technique where RAM nodes f...
This paper presents a survey of a class of neural models known as Weightless Neural Networks (WNNs)....
This thesis brings together two strands of neural networks research - weightless systems and statis...
A collection of hardware weightless Boolean elements has been developed. These form fundamental bui...
A collection of hardware weightless Boolean elements has been developed. These form fundamental buil...
The long course of evolution has given the human brain many desirable characteristics not present in...
A new architecture for networks of RAM-based Boolean neurons is presented which, whilst retaining le...
The use of n-tuple or weightless neural networks as pattern recognition devices i well known (Aleksa...
This work is based on a logical neuron model without weights, the Random Access Memory [1]. For the ...
Abstract. This chapter outlines the research, development and perspectives of quantum neural network...
The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleks...
The standard multi layer perceptron neural network (MLPNN) type has various drawbacks, one of which ...
Abstract. By embedding the boolean space Z2 as an orthonormal basis in a vec-tor space we can treat ...
Artificial neural net (ANN) models, or neural networks, connectionist models, parallel distributed p...
Artificial Neural Networks (ANNs) have been developed in an attempt to emulate the information proce...
Weightless neural networks (WNNs) are an alternative pattern recognition technique where RAM nodes f...
This paper presents a survey of a class of neural models known as Weightless Neural Networks (WNNs)....
This thesis brings together two strands of neural networks research - weightless systems and statis...
A collection of hardware weightless Boolean elements has been developed. These form fundamental bui...
A collection of hardware weightless Boolean elements has been developed. These form fundamental buil...
The long course of evolution has given the human brain many desirable characteristics not present in...
A new architecture for networks of RAM-based Boolean neurons is presented which, whilst retaining le...
The use of n-tuple or weightless neural networks as pattern recognition devices i well known (Aleksa...
This work is based on a logical neuron model without weights, the Random Access Memory [1]. For the ...
Abstract. This chapter outlines the research, development and perspectives of quantum neural network...
The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleks...
The standard multi layer perceptron neural network (MLPNN) type has various drawbacks, one of which ...
Abstract. By embedding the boolean space Z2 as an orthonormal basis in a vec-tor space we can treat ...
Artificial neural net (ANN) models, or neural networks, connectionist models, parallel distributed p...
Artificial Neural Networks (ANNs) have been developed in an attempt to emulate the information proce...
Weightless neural networks (WNNs) are an alternative pattern recognition technique where RAM nodes f...