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A new criterion for modeling systems

  • Lawrence W. TaylorJr.
System Modeling And Identification
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3)

Keywords

Unknown Parameter Candidate Model Automatic Control System Response Error Calculated Response 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Balakrishnan, A. V.: Communication Theory. McGraw-Hill Book Company, C. 1968. IFAC Symposium 1967 on the Problems of Identification in Automatic Control Systems (Prague, Czechoslovakia), June 12–17, 1967.Google Scholar
  2. 2.
    Cuenod, M., and Sage, A. P.: Comparison of Some Methods Used for Process Identification. IFAC Symposium 1967 on the Problems of Identification in Automatic Control Systems (Prague, Czechoslovakia), June 12–17, 1967.Google Scholar
  3. 3.
    Eykhoff, P.: Process Parameter and State Estimation. IFAC Symposium 1967 on the Problems of Identification in Automatic Control Systems (Prague, Czechoslovakia), June 12–17, 1967.Google Scholar
  4. 4.
    Taylor, Lawrence W., Jr.: Nonlinear Time-Domain Models of Human Controllers. Hawaii International Conference on System Sciences (Honolulu, Hawaii), January 29–31, 1968.Google Scholar
  5. 5.
    Taylor, Lawrence W., Jr., and Iliff, Kenneth W.: Systems Identification Using a Modified Newton-Raphson Method — A Fortran Program. NASA TN D-6734, May 1972.Google Scholar
  6. 6.
    Taylor, Lawrence W., Jr.: How Complex Should a Model Be? 1970 Joint Automatic Control Conference (Atlanta, Georgia), June 24–26, 1970.Google Scholar
  7. 7.
    Akaike, H.: Statistical Predictor Identification. Ann. Inst. Statist. Math., Vol. 22, 1970.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1973

Authors and Affiliations

  • Lawrence W. TaylorJr.
    • 1
  1. 1.NASA Langley Research CenterHampton

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