Linear interconnection architecture in parallel implementation of neural network models

M. Taghi Mostafavi

doi:10.1117/12.47757

1 March 1991 Linear interconnection architecture in parallel implementation of neural network models

M. Taghi Mostafavi

Proceedings Volume 1396, Applications of Optical Engineering: Proceedings of OE/Midwest '90; (1991) https://doi.org/10.1117/12.47757
Event: Applications of Optical Engineering: Proceedings of OE/Midwest '90, 1990, Rosemont, IL, United States

Abstract

An architecture for VLSI/ULSI implementation of neural network models is presented. The architecture is of the linear and systolic type and can easily be expanded to a larger network size with more processing elements per layer and/or more layers per network model. The weights in this architecture are fully adjustable. The weights must be pre-computed with the help of a host computer and downloaded to the system as a preinitialized process. This architecture is basically suitable for feed forward neural network architecture. 1.

Citation Download Citation

M. Taghi Mostafavi "Linear interconnection architecture in parallel implementation of neural network models", Proc. SPIE 1396, Applications of Optical Engineering: Proceedings of OE/Midwest '90, (1 March 1991); https://doi.org/10.1117/12.47757

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