Systolic implementation of neural networks

Systolic implementation of neural networks

Systolic implementation of neural networks is suggested. These arrays do not suffer from long feedback connections. Various learning rules are incorporated in the suggested systolic implementation of neural networks. It is shown that these arrays can be easily generalized for multilayered feedforwar...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Zubair, M., Madan, B.B.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Computational modeling
Computer networks
Feedforward neural networks
Hopfield neural networks
Multi-layer neural network
Neural networks
Neurofeedback
Neurons
Optical computing
Optical feedback
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Beschreibung
Zusammenfassung:Systolic implementation of neural networks is suggested. These arrays do not suffer from long feedback connections. Various learning rules are incorporated in the suggested systolic implementation of neural networks. It is shown that these arrays can be easily generalized for multilayered feedforward networks.< >
DOI:10.1109/ICCD.1989.63412