• DocumentCode
    1306381
  • Title

    Generalized entropy and minimum system complexity

  • Author

    Pandelidis, Ioannis

  • Author_Institution
    Dept. of Mech. Eng., Maryland Univ., College Park, MD, USA
  • Volume
    20
  • Issue
    5
  • fYear
    1990
  • Firstpage
    1234
  • Lastpage
    1238
  • Abstract
    The problem of characterizing information processing systems in terms of their entropic complexity is examined. Automatic control systems and the design/manufacturing process are seen as such systems, so that the results of such research are intended primarily for this area. The concept of generalized entropy is introduced in order to unify the treatment of continuous and discrete signals and the corresponding information processing systems. Given a level of entropic complexity of the reference and disturbance inputs to a system, the author derives minimum entropic complexity requirements for that system. It is assumed that the entropic system complexity that is defined by the author is monotonically related to cost. Based on this assumption and a previously proposed design/manufacturing axiom, the system having minimum entropic complexity is derived
  • Keywords
    control system analysis; information theory; manufacturing processes; design/manufacturing process; entropic complexity; entropy; information processing systems; minimum system complexity; Adaptive systems; Artificial intelligence; Artificial neural networks; Associative memory; Cost accounting; Entropy; Fuzzy logic; Information processing; Learning systems; Neural networks;
  • fLanguage
    English
  • Journal_Title
    Systems, Man and Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9472
  • Type

    jour

  • DOI
    10.1109/21.59987
  • Filename
    59987