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
Data-Driven Symbol Detection Via Model-Based Machine Learni..:
, In:
2021 IEEE Statistical Signal Processing Workshop (SSP)
,
Farsad, Nariman
;
Shlezinger, Nir
;
Goldsmith, Andrea J.
. - p. 571-575 , 2021
Link:
https://doi.org/10.1109/SSP49050.2021.9513859
RT T1
2021 IEEE Statistical Signal Processing Workshop (SSP)
: T1
Data-Driven Symbol Detection Via Model-Based Machine Learning
UL https://suche.suub.uni-bremen.de/peid=ieee-9513859&Exemplar=1&LAN=DE A1 Farsad, Nariman A1 Shlezinger, Nir A1 Goldsmith, Andrea J. A1 Eldar, Yonina C. YR 2021 SN 2693-3551 K1 Machine learning algorithms K1 Uncertainty K1 Viterbi algorithm K1 Computational modeling K1 Signal processing algorithms K1 Training data K1 Receivers SP 571 OP 575 LK http://dx.doi.org/https://doi.org/10.1109/SSP49050.2021.9513859 DO https://doi.org/10.1109/SSP49050.2021.9513859 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)