Dataset supporting the paper entitled “Low-Power 3D Integration using Inductive Coupling Links for Neurotechnology Applications"
Dataset supporting the paper entitled “Low-Power 3D Integration using Inductive Coupling Links for Neurotechnology Applications"
This dataset supports the article entitled 'Low-Power 3D Integration using Inductive Coupling Links for Neurotechnology Applications' accepted for publication in Design, Automation & Test in Europe Conference & Exhibition (DATE), Dresden, 2018.
3D-IC, Neurotechnology
University of Southampton
Fletcher, Benjamin, James
b9ee2f3f-f125-47df-a73e-e61c0404d4c9
Das, Shidhartha
c1e693af-261c-495d-8f0f-227396df0e3b
Poon, Chi-Sang
9956b00e-5e38-4a0b-b6bd-b17ea08f4dcf
Mak, Terrence
0f90ac88-f035-4f92-a62a-7eb92406ea53
Fletcher, Benjamin, James
b9ee2f3f-f125-47df-a73e-e61c0404d4c9
Das, Shidhartha
c1e693af-261c-495d-8f0f-227396df0e3b
Poon, Chi-Sang
9956b00e-5e38-4a0b-b6bd-b17ea08f4dcf
Mak, Terrence
0f90ac88-f035-4f92-a62a-7eb92406ea53
Fletcher, Benjamin, James, Das, Shidhartha, Poon, Chi-Sang and Mak, Terrence
(2017)
Dataset supporting the paper entitled “Low-Power 3D Integration using Inductive Coupling Links for Neurotechnology Applications".
University of Southampton
doi:10.5258/SOTON/D0318
[Dataset]
Abstract
This dataset supports the article entitled 'Low-Power 3D Integration using Inductive Coupling Links for Neurotechnology Applications' accepted for publication in Design, Automation & Test in Europe Conference & Exhibition (DATE), Dresden, 2018.
Spreadsheet
DataSet.xlsx
- Dataset
More information
Published date: 22 November 2017
Keywords:
3D-IC, Neurotechnology
Organisations:
Electronics & Computer Science, Electronic & Software Systems
Identifiers
Local EPrints ID: 415877
URI: http://eprints.soton.ac.uk/id/eprint/415877
PURE UUID: 6a84169c-1a56-4e78-8ee4-92404d1f092f
Catalogue record
Date deposited: 27 Nov 2017 17:31
Last modified: 05 Nov 2023 09:20
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Contributors
Creator:
Benjamin, James Fletcher
Creator:
Shidhartha Das
Creator:
Chi-Sang Poon
Creator:
Terrence Mak
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