The formal neural networks represent a new view on ICT. The original neural network was based on the work by Warren McCulloch and Walter Pitts published in 1943. The most important issue in investigating neural networks is to consider how they may learn. Various kinds of artificial neuron based on the McCulloch-Pitts unit will now be described, and several learning rules discussed. The Linear Threshold Unit We have discussed in the classical neuron and the simple, on/off threshold unit. As McCulloch-Pitts had demonstrated in the early 1940s, to a first approximation, networks of such units can perform arbitrary computations
This thesis investigates the functionality of the units used in connectionist Artificial Intelligenc...
Author presents concept and historical outline of the development of the artificial neuronal network...
This report surveys some connections between Boolean functions and artificial neural networks. The f...
Neural Network models have received increased attention in the recent years. Aimed at achieving huma...
I li.i DISTRIBUIYTON AVAILABILITY STATE MEK 1ýc. DISTRIBUTION COOL Approved for public release; Dist...
Artificial neural networks (ANN) is referred as the neural networks are the signal processing and in...
An overview of neural networks, covering multilayer perceptrons, radial basis functions, constructiv...
The models of the computing for the perform the pattern recognition methods by the performance and t...
This paper presents a new approach to mental functions modeling with the use of artificial neural ne...
A neuron network is a computational model based on structure and functions of biological neural netw...
The basic structure and definitions of artificial neural networks are exposed, as an introduction to...
Artificial neural networks are 'biologically' inspired networks.They have the ability to learn from ...
Neural network is a web of million numbers of inter-connected neurons which executes parallel proces...
Artificial neural net (ANN) models, or neural networks, connectionist models, parallel distributed p...
Part 1: Invited PaperInternational audienceThe history of neural networks can be traced back to the ...
This thesis investigates the functionality of the units used in connectionist Artificial Intelligenc...
Author presents concept and historical outline of the development of the artificial neuronal network...
This report surveys some connections between Boolean functions and artificial neural networks. The f...
Neural Network models have received increased attention in the recent years. Aimed at achieving huma...
I li.i DISTRIBUIYTON AVAILABILITY STATE MEK 1ýc. DISTRIBUTION COOL Approved for public release; Dist...
Artificial neural networks (ANN) is referred as the neural networks are the signal processing and in...
An overview of neural networks, covering multilayer perceptrons, radial basis functions, constructiv...
The models of the computing for the perform the pattern recognition methods by the performance and t...
This paper presents a new approach to mental functions modeling with the use of artificial neural ne...
A neuron network is a computational model based on structure and functions of biological neural netw...
The basic structure and definitions of artificial neural networks are exposed, as an introduction to...
Artificial neural networks are 'biologically' inspired networks.They have the ability to learn from ...
Neural network is a web of million numbers of inter-connected neurons which executes parallel proces...
Artificial neural net (ANN) models, or neural networks, connectionist models, parallel distributed p...
Part 1: Invited PaperInternational audienceThe history of neural networks can be traced back to the ...
This thesis investigates the functionality of the units used in connectionist Artificial Intelligenc...
Author presents concept and historical outline of the development of the artificial neuronal network...
This report surveys some connections between Boolean functions and artificial neural networks. The f...