DocumentCode
1867266
Title
Statistical signatures for self-adaptive sensing
Author
Price, E.I. ; Reece, S. ; Probert-Smith, P.
Author_Institution
Dept. of Eng. Sci., Oxford Univ., UK
fYear
2001
fDate
2001
Firstpage
141
Lastpage
146
Abstract
Designing signal processing software is difficult. it is difficult because the world is unpredictable and it is impossible to guarantee software reliability in unforeseen circumstances. Further, it is difficult to anticipate sensor behaviour, as ambient conditions-for example, lighting or weather, can affect the data they output in a multitude of ways. Autonomous, on-line, self-adaptive image processing software is required, that can be adjusted when novel sensing environments are encountered. The appropriate choice of sensor and signal processing tools is a matter of context and the contextual consensus that is available within the framework of a multiple sensor system.
Keywords
adaptive systems; image processing; online operation; sensor fusion; statistical analysis; ambient conditions; autonomous online self-adaptive image processing software; contextual consensus; multiple sensor system; self-adaptive sensing; signal processing software design; signal processing tools; statistical signatures; Adaptive signal processing; Design engineering; Process design; Reliability engineering; Robot sensing systems; Sensor phenomena and characterization; Sensor systems; Signal processing; Signal processing algorithms; Software design;
fLanguage
English
Publisher
ieee
Conference_Titel
Multisensor Fusion and Integration for Intelligent Systems, 2001. MFI 2001. International Conference on
Print_ISBN
3-00-008260-3
Type
conf
DOI
10.1109/MFI.2001.1013522
Filename
1013522
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