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Using neural net architectures in analog circuits

Publication ,  Journal Article
Brooke, MA
Published in: Midwest Symposium on Circuits and Systems
December 1, 2007

A method of using parallel analog building blocks with adjustable parameters was demonstrated to be able to achieve a wide array of analog circuit functionally with high accuracy. The method is generally useful when the penalty for needing to adapt the circuit to achieve performance is out weighted by the advantages in speed and power dissipation achievable by reducing the design constraints on the parallel building blocks which need not be very predictable. ©2007 IEEE.

Duke Scholars

Published In

Midwest Symposium on Circuits and Systems

DOI

ISSN

1548-3746

Publication Date

December 1, 2007

Start / End Page

1018 / 1021
 

Citation

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Brooke, M. A. (2007). Using neural net architectures in analog circuits. Midwest Symposium on Circuits and Systems, 1018–1021. https://doi.org/10.1109/MWSCAS.2007.4488735
Brooke, M. A. “Using neural net architectures in analog circuits.” Midwest Symposium on Circuits and Systems, December 1, 2007, 1018–21. https://doi.org/10.1109/MWSCAS.2007.4488735.
Brooke MA. Using neural net architectures in analog circuits. Midwest Symposium on Circuits and Systems. 2007 Dec 1;1018–21.
Brooke, M. A. “Using neural net architectures in analog circuits.” Midwest Symposium on Circuits and Systems, Dec. 2007, pp. 1018–21. Scopus, doi:10.1109/MWSCAS.2007.4488735.
Brooke MA. Using neural net architectures in analog circuits. Midwest Symposium on Circuits and Systems. 2007 Dec 1;1018–1021.

Published In

Midwest Symposium on Circuits and Systems

DOI

ISSN

1548-3746

Publication Date

December 1, 2007

Start / End Page

1018 / 1021