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
Quantized robust filtering of semi-Markov jump systems with..:
, In:
2022 China Automation Congress (CAC)
,
Wang, Qiyi
;
Peng, Li
;
Yang, Shenhao
- p. 1425-1430 , 2022
Link:
https://doi.org/10.1109/CAC57257.2022.10055611
RT T1
2022 China Automation Congress (CAC)
: T1
Quantized robust filtering of semi-Markov jump systems with random measurement data dropouts
UL https://suche.suub.uni-bremen.de/peid=ieee-10055611&Exemplar=1&LAN=DE A1 Wang, Qiyi A1 Peng, Li A1 Yang, Shenhao YR 2022 SN 2688-0938 K1 Maximum likelihood detection K1 Estimation error K1 Quantization (signal) K1 Automation K1 Filtering K1 Nonlinear filters K1 Numerical simulation K1 semi-Markov jump systems K1 data dropouts K1 quantizer K1 H∞ performance SP 1425 OP 1430 LK http://dx.doi.org/https://doi.org/10.1109/CAC57257.2022.10055611 DO https://doi.org/10.1109/CAC57257.2022.10055611 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)