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Neural network implementation using a single MOST per synapse
- Source :
- IEEE Transactions on Neural Networks. 6:1008-1011
- Publication Year :
- 1995
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 1995.
-
Abstract
- A VLSI implementation of an artificial neural network using a single n-channel MOS (metal-oxide semiconductor) transistor per synapse is investigated. The simplicity of the design is achieved by using pulse width modulation to represent neural activity and by using a novel technique to manipulate negative weights. A simple multilayer perceptron (MLP) network was simulated using the SPICE circuit simulator and the performance of a hardware realization of the same MLP network was measured. Simulations and measurements are shown to agree well. >
- Subjects :
- Very-large-scale integration
Artificial neural network
Computer Networks and Communications
business.industry
Computer science
Computer Science::Neural and Evolutionary Computation
Transistor
Hardware_PERFORMANCEANDRELIABILITY
General Medicine
Integrated circuit
Perceptron
Computer Science Applications
law.invention
Synapse
Computer Science::Hardware Architecture
Computer Science::Emerging Technologies
Artificial Intelligence
law
Multilayer perceptron
Embedded system
Hardware_INTEGRATEDCIRCUITS
Electronic engineering
business
Software
Hardware_LOGICDESIGN
Subjects
Details
- ISSN :
- 10459227
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Neural Networks
- Accession number :
- edsair.doi.dedup.....8e36220895cb316ac9530a2a74e9518c
- Full Text :
- https://doi.org/10.1109/72.392265