Accurate design of analog CNN in CMOS digital technologies
- 4 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 273-280
- https://doi.org/10.1109/cnna.1990.207532
Abstract
Explores the design of cellular neural networks (CNN) by using sampled-data analog current-mode techniques which neither requires capacitors nor resistors but just MOS transistors. The feature makes the proposed technique well suited for implementation in conventional VLSI MOS technologies. A set of building blocks is presented and their performance validated by device-level simulation results. Also, guidelines are given concerning the choice of the circuit parameters for optimum operation.Keywords
This publication has 8 references indexed in Scilit:
- Analog signal processing using cellular neural networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- VLSI implementation of cellular neural networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Nonlinear switched capacitor 'neural' networks for optimization problemsIEEE Transactions on Circuits and Systems, 1990
- Analog VLSI Implementation of Neural SystemsPublished by Springer Nature ,1989
- Cellular neural networks: applicationsIEEE Transactions on Circuits and Systems, 1988
- Cellular neural networks: theoryIEEE Transactions on Circuits and Systems, 1988
- An introduction to computing with neural netsIEEE ASSP Magazine, 1987
- Simple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuitIEEE Transactions on Circuits and Systems, 1986