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.
Advances on Weightless Neural Systems
M De Gregorio;
2014
Abstract
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.File in questo prodotto:
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