I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
A Method for ACM on Q/V-Band Satellite Links Based on Artif..:
, In:
2020 10th Advanced Satellite Multimedia Systems Conference and the 16th Signal Processing for Space Communications Workshop (ASMS/SPSC)
,
Ebert, Johannes
;
Bailer, Werner
;
Flavio, Joel
.. - p. 1-5 , 2020
Link:
https://doi.org/10.1109/ASMS/SPSC48805.2020.9268889
RT T1
2020 10th Advanced Satellite Multimedia Systems Conference and the 16th Signal Processing for Space Communications Workshop (ASMS/SPSC)
: T1
A Method for ACM on Q/V-Band Satellite Links Based on Artificial Intelligence
UL https://suche.suub.uni-bremen.de/peid=ieee-9268889&Exemplar=1&LAN=DE A1 Ebert, Johannes A1 Bailer, Werner A1 Flavio, Joel A1 Plimon, Karin A1 Winter, Martin YR 2020 SN 2326-5949 K1 Signal to noise ratio K1 Time series analysis K1 Vegetation K1 Training K1 Switches K1 Rain K1 Forestry K1 Adaptive coding and modulation K1 Q/V-band K1 machine learning K1 artificial intelligence SP 1 OP 5 LK http://dx.doi.org/https://doi.org/10.1109/ASMS/SPSC48805.2020.9268889 DO https://doi.org/10.1109/ASMS/SPSC48805.2020.9268889 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)