• 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