By Topic

Uncertainty-management-network-based dynamic sensor model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Park, S. ; Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA ; Lee, C.S.G.

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

Published in:

Multisensor Fusion and Integration for Intelligent Systems, 1994. IEEE International Conference on MFI '94.

Date of Conference:

2-5 Oct 1994