Floating-Point Approximation Enabling Cost-Effective and High-Precision Digital Implementation of FitzHugh-Nagumo Neural Networks-Reference-Cited by-同舟云学术

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Floating-Point Approximation Enabling Cost-Effective and High-Precision Digital Implementation of FitzHugh-Nagumo Neural Networks

Published:2023 Issue: Volume: Page:1-15
ISSN:1932-4545
Container-title:IEEE Transactions on Biomedical Circuits and Systems
language:
Short-container-title:IEEE Trans. Biomed. Circuits Syst.

Author:

Zuo Y.¹,Ning N.¹^ORCID,Qiao G. C.¹^ORCID,Wu J. H.¹,Bao J. H.¹^ORCID,Zhang X. Y.²,Bai J.²,Wu F. H.¹,Liu Y.¹^ORCID,Yu Q.¹^ORCID,Hu S. G.¹^ORCID

Affiliation:

1. State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, P. R. China

2. Laboratory of Science and Technology on Millmetre-Wave, Beijing Institute of Remote-Sensing Equipment, Beijing, P. R. China

Funder

STI

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Biomedical Engineering

Link

http://xplorestaging.ieee.org/ielx7/4156126/4358093/10295563.pdf?arnumber=10295563

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