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  • 1
    Online Resource
    Online Resource
    Introduction and implementations of the kalman filter (2019)
    London : IntechOpen
    Details
    UID:
    b3kat_BV046104724
    Format: 1 Online-Ressource , Illustrationen, Diagramme
    ISBN: 9781838805371 , 9781838807399
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-1-83880-536-4
    Language: English
    DOI: 10.5772/intechopen.75731
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Author information: Govaers, Felix
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    Fulltext
    Fulltext
    Fulltext
    EUV Frankfurt
    HTW Berlin
    TH Wildau
  • 2
    Online Resource
    Online Resource
    Introduction and Implementations of the Kalman Filter (2019)
    [Erscheinungsort nicht ermittelbar] : IntechOpen
    Details
    UID:
    gbv_1778491715
    Format: 1 Online-Ressource (128 p.)
    ISBN: 9781838805364 , 9781838807399 , 9781838805371
    Content: Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some ""awareness"" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not
    Note: English
    Language: English
    URL: kostenfrei
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    Stabi Berlin
    UB Potsdam
  • 3
    Online Resource
    Online Resource
    Introduction and Implementations of the Kalman Filter (2019)
    [Erscheinungsort nicht ermittelbar] : IntechOpen
    Details
    UID:
    gbv_1877755834
    Format: 1 Online-Ressource (128 p.)
    ISBN: 9781838805371 , 9781838805364 , 9781838807399
    Content: Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some "awareness" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not
    Note: English
    Language: Undetermined
    URL: kostenfrei
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    Stabi Berlin
  • 4
    Online Resource
    Online Resource
    Introduction and implementations of the kalman filter / (2019)
    IntechOpen | London, England :IntechOpen,
    Details
    UID:
    edoccha_9959074368702883
    Format: 1 online resource (128 pages) : , illustrations
    ISBN: 1-83880-739-X , 1-83880-537-0
    Content: Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some ""awareness"" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.
    Note: English
    Additional Edition: ISBN 1-83880-536-2
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Charité
  • 5
    Online Resource
    Online Resource
    Introduction and implementations of the kalman filter / (2019)
    IntechOpen | London, England :IntechOpen,
    Details
    UID:
    almahu_9949607162502882
    Format: 1 online resource (128 pages) : , illustrations
    ISBN: 1-83880-739-X , 1-83880-537-0
    Content: Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some ""awareness"" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.
    Note: English
    Additional Edition: ISBN 1-83880-536-2
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    HU Berlin
  • 6
    Online Resource
    Online Resource
    Introduction and implementations of the kalman filter / (2019)
    IntechOpen | London, England :IntechOpen,
    Details
    UID:
    edocfu_9959074368702883
    Format: 1 online resource (128 pages) : , illustrations
    ISBN: 1-83880-739-X , 1-83880-537-0
    Content: Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some ""awareness"" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.
    Note: English
    Additional Edition: ISBN 1-83880-536-2
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    FU Berlin
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