DocumentCode :
2669825
Title :
Uncertainty-management-network-based dynamic sensor model
Author :
Park, Sangwook ; Lee, C. S George
Author_Institution :
Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
fYear :
1994
fDate :
2-5 Oct 1994
Firstpage :
222
Lastpage :
229
Abstract :
The raw data obtained by physical sensors are initially modeled using fuzzy numbers which are then processed by the subsequent uncertainty management network (UMN) which is a new paradigm in propagating uncertainties through a sensor system model. The UMN partitions the processing blocks of the sensor system into a tree-like network structure of basic processing nodes which perform elementary arithmetic, logical, aggregation, or branching operations interconnected using multiple information propagation channels. The UMN allows the dynamic modelling of sensor systems by providing a confidence measure for the output of the sensor system which incorporates the changing conditions of the environment as well as the changes occurring within the sensor system itself. An example of an UMN-based vision system is illustrated to clarify the idea and the concepts
Keywords :
computer vision; fuzzy set theory; sensor fusion; uncertainty handling; dynamic modelling; dynamic sensor model; fuzzy numbers; multiple information propagation channels; tree-like network structure; uncertainty-management-network; vision system; Arithmetic; Engineering management; Fuzzy sets; Fuzzy systems; Information processing; Intelligent networks; Probability density function; Sensor fusion; Sensor systems; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 1994. IEEE International Conference on MFI '94.
Conference_Location :
Las Vegas, NV
Print_ISBN :
0-7803-2072-7
Type :
conf
DOI :
10.1109/MFI.1994.398449
Filename :
398449
Link To Document :
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