To train a Boolean neural network to comment on the progress of the task it is controlling, we have implemented in the network an Hebbian rule with the help of the node assemblies. Actually, our network can comment also on its communications with us without any danger to enter in a loop-like endeless activit
Logic programming is carried out on a neural network. A higher-order Hopfield neural network is used...
Based on the assumption that there exists a neu-ral network that efficiently represents a set of Boo...
We investigate the properties of an unsupervised neural network which uses simple Hebbian learning a...
To train a Boolean neural network to comment on the progress of the task it is controlling, we have ...
In this paper a Boolean neural networks which is able to learn and to control temporal sequences of ...
The classical exclusive-or problem and many others like it cannot be performed with networks without...
We discuss the adaptable Boolean net neural paradigm together with its learning and generalization p...
Usually the Hebbian learning spontaneously seems to produce associative memory behaviour in the netw...
Here, we discuss a Boolean neural networks which is able to learn and to control temporal sequences ...
A multi-layered neural assembly is developed which has the capability of learning arbitrary Boolean ...
Human decisional processes result from the employment of selected quantities of relevant information...
A fundamental aspect of learning in biological neural networks is the plasticity property which allo...
A new architecture for networks of RAM-based Boolean neurons is presented which, whilst retaining le...
Boolean networks (BNs) have been mainly considered as genetic regulatory network modelsand are the s...
This report surveys some connections between Boolean functions and artificial neural networks. The f...
Logic programming is carried out on a neural network. A higher-order Hopfield neural network is used...
Based on the assumption that there exists a neu-ral network that efficiently represents a set of Boo...
We investigate the properties of an unsupervised neural network which uses simple Hebbian learning a...
To train a Boolean neural network to comment on the progress of the task it is controlling, we have ...
In this paper a Boolean neural networks which is able to learn and to control temporal sequences of ...
The classical exclusive-or problem and many others like it cannot be performed with networks without...
We discuss the adaptable Boolean net neural paradigm together with its learning and generalization p...
Usually the Hebbian learning spontaneously seems to produce associative memory behaviour in the netw...
Here, we discuss a Boolean neural networks which is able to learn and to control temporal sequences ...
A multi-layered neural assembly is developed which has the capability of learning arbitrary Boolean ...
Human decisional processes result from the employment of selected quantities of relevant information...
A fundamental aspect of learning in biological neural networks is the plasticity property which allo...
A new architecture for networks of RAM-based Boolean neurons is presented which, whilst retaining le...
Boolean networks (BNs) have been mainly considered as genetic regulatory network modelsand are the s...
This report surveys some connections between Boolean functions and artificial neural networks. The f...
Logic programming is carried out on a neural network. A higher-order Hopfield neural network is used...
Based on the assumption that there exists a neu-ral network that efficiently represents a set of Boo...
We investigate the properties of an unsupervised neural network which uses simple Hebbian learning a...
DOI
Add to ORKG