Impact of the Dictionary Mismatch for CS-based DOA Estimation
8 Angebote vergleichen
| Preise | 2014 | 2015 | 2019 |
|---|---|---|---|
| Schnitt | € 33,06 | € 38,29 | € 31,85 |
| Nachfrage |
1
Symbolbild
Impact of the Dictionary Mismatch for CS-based DOA Estimation (2014)
DE PB NW RPISBN: 9783639676372 bzw. 3639676378, in Deutsch, Av Akademikerverlag Sep 2014, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, NDS, Germany.
This item is printed on demand - Print on Demand Titel. Neuware - The problem of direction finding has primal importance in modern life. Today, smart direction finding systems are used in various technical fields such as RADAR, SONAR, interference reduction, multi-user or multi-channel data transmission, environmental sounding, medical purposes and in many other areas of human life. Recent achievements in the field of signal processing provide a new paradigm known as Compressed Sensing (CS), where the advantages of sparse signal representation are utilized. The DOA model can be also formulated as sparse, i.e. with reduced measurement effort of the antenna. This all brings a high potential for CS to be applied to a DOA estimation. The focus of this thesis is an in-depth analysis of the impact of the off-the-grid CS-based DOA model mismatch on the recovery process and the development of an efficient CS-based DOA estimator able to provide a stable performance even for a realistic scenario with true signal locations. Brief details related to this work are provided below. Course of Studies: Communications and Signal Processing; Department: Digital Broadcasting Research Laboratory; Responsible Professor: Univ.-Prof. Dr.-Ing. Giovanni Del Galdo; Supervisor: Dr.-Ing. Florian Roemer 116 pp. Englisch.
This item is printed on demand - Print on Demand Titel. Neuware - The problem of direction finding has primal importance in modern life. Today, smart direction finding systems are used in various technical fields such as RADAR, SONAR, interference reduction, multi-user or multi-channel data transmission, environmental sounding, medical purposes and in many other areas of human life. Recent achievements in the field of signal processing provide a new paradigm known as Compressed Sensing (CS), where the advantages of sparse signal representation are utilized. The DOA model can be also formulated as sparse, i.e. with reduced measurement effort of the antenna. This all brings a high potential for CS to be applied to a DOA estimation. The focus of this thesis is an in-depth analysis of the impact of the off-the-grid CS-based DOA model mismatch on the recovery process and the development of an efficient CS-based DOA estimator able to provide a stable performance even for a realistic scenario with true signal locations. Brief details related to this work are provided below. Course of Studies: Communications and Signal Processing; Department: Digital Broadcasting Research Laboratory; Responsible Professor: Univ.-Prof. Dr.-Ing. Giovanni Del Galdo; Supervisor: Dr.-Ing. Florian Roemer 116 pp. Englisch.
2
Impact of the Dictionary Mismatch for CS-based DOA Estimation
~EN NW ABISBN: 9783639676372 bzw. 3639676378, vermutlich in Englisch, VDM Verlag Dr. Müller, Saarbrücken, Deutschland, neu, Hörbuch.
Lieferung aus: Österreich, Lieferzeit: 5 Tage, zzgl. Versandkosten.
The problem of direction finding has primal importance in modern life. Today, smart direction finding systems are used in various technical fields such as RADAR, SONAR, interference reduction, multi-user or multi-channel data transmission, environmental sounding, medical purposes and in many other areas of human life. Recent achievements in the field of signal processing provide a new paradigm known as Compressed Sensing (CS), where the advantages of sparse signal representation are utilized. The DOA model can be also formulated as sparse, i.e. with reduced measurement effort of the antenna. This all brings a high potential for CS to be applied to a DOA estimation. The focus of this thesis is an in-depth analysis of the impact of the off-the-grid CS-based DOA model mismatch on the recovery process and the development of an efficient CS-based DOA estimator able to provide a stable performance even for a realistic scenario with true signal locations. Brief details related to this work are provided below. Course of Studies: Communications and Signal Processing, Department: Digital Broadcasting Research Laboratory, Responsible Professor: Univ.-Prof. Dr.-Ing. Giovanni Del Galdo, Supervisor: Dr.-Ing. Florian Roemer.
The problem of direction finding has primal importance in modern life. Today, smart direction finding systems are used in various technical fields such as RADAR, SONAR, interference reduction, multi-user or multi-channel data transmission, environmental sounding, medical purposes and in many other areas of human life. Recent achievements in the field of signal processing provide a new paradigm known as Compressed Sensing (CS), where the advantages of sparse signal representation are utilized. The DOA model can be also formulated as sparse, i.e. with reduced measurement effort of the antenna. This all brings a high potential for CS to be applied to a DOA estimation. The focus of this thesis is an in-depth analysis of the impact of the off-the-grid CS-based DOA model mismatch on the recovery process and the development of an efficient CS-based DOA estimator able to provide a stable performance even for a realistic scenario with true signal locations. Brief details related to this work are provided below. Course of Studies: Communications and Signal Processing, Department: Digital Broadcasting Research Laboratory, Responsible Professor: Univ.-Prof. Dr.-Ing. Giovanni Del Galdo, Supervisor: Dr.-Ing. Florian Roemer.
3
Impact of the Dictionary Mismatch for CS-based DOA Estimation
~EN PB NWISBN: 9783639676372 bzw. 3639676378, vermutlich in Englisch, AV Akademikerverlag, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Impact of the Dictionary Mismatch for CS-based DOA Estimation: The problem of direction finding has primal importance in modern life. Today, smart direction finding systems are used in various technical fields such as RADAR, SONAR, interference reduction, multi-user or multi-channel data transmission, environmental sounding, medical purposes and in many other areas of human life. Recent achievements in the field of signal processing provide a new paradigm known as Compressed Sensing (CS), where the advantages of sparse signal representation are utilized. The DOA model can be also formulated as sparse, i.e. with reduced measurement effort of the antenna. This all brings a high potential for CS to be applied to a DOA estimation. The focus of this thesis is an in-depth analysis of the impact of the off-the-grid CS-based DOA model mismatch on the recovery process and the development of an efficient CS-based DOA estimator able to provide a stable performance even for a realistic scenario with true signal locations. Brief details related to this work are provided below. Course of Studies: Communications and Signal Processing Department: Digital Broadcasting Research Laboratory Responsible Professor: Univ.-Prof. Dr.-Ing. Giovanni Del Galdo Supervisor: Dr.-Ing. Florian Roemer, Englisch, Taschenbuch.
Impact of the Dictionary Mismatch for CS-based DOA Estimation: The problem of direction finding has primal importance in modern life. Today, smart direction finding systems are used in various technical fields such as RADAR, SONAR, interference reduction, multi-user or multi-channel data transmission, environmental sounding, medical purposes and in many other areas of human life. Recent achievements in the field of signal processing provide a new paradigm known as Compressed Sensing (CS), where the advantages of sparse signal representation are utilized. The DOA model can be also formulated as sparse, i.e. with reduced measurement effort of the antenna. This all brings a high potential for CS to be applied to a DOA estimation. The focus of this thesis is an in-depth analysis of the impact of the off-the-grid CS-based DOA model mismatch on the recovery process and the development of an efficient CS-based DOA estimator able to provide a stable performance even for a realistic scenario with true signal locations. Brief details related to this work are provided below. Course of Studies: Communications and Signal Processing Department: Digital Broadcasting Research Laboratory Responsible Professor: Univ.-Prof. Dr.-Ing. Giovanni Del Galdo Supervisor: Dr.-Ing. Florian Roemer, Englisch, Taschenbuch.
4
Symbolbild
Impact of the Dictionary Mismatch for CS-based DOA Estimation (2014)
DE NWISBN: 9783639676372 bzw. 3639676378, in Deutsch, AV Akademikerverlag, neu.
Von Händler/Antiquariat, PBShop [61989342], Secaucus, NJ, U.S.A.
New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
5
Impact of the Dictionary Mismatch for CS-based DOA Estimation
~EN PB NWISBN: 3639676378 bzw. 9783639676372, vermutlich in Englisch, AV Akademikerverlag, Taschenbuch, neu.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
7
Impact of the Dictionary Mismatch for CS-based DOA Estimation (2014)
~EN PB NWISBN: 9783639676372 bzw. 3639676378, vermutlich in Englisch, VDM Verlag Dr. Müller, Saarbrücken, Deutschland, Taschenbuch, neu.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Lade…