• DocumentCode
    1031869
  • Title

    Feedback stabilization using two-hidden-layer nets

  • Author

    Sontag, Eduardo D.

  • Author_Institution
    Dept. of Math., Rutgers Univ., New Brunswick, NJ, USA
  • Volume
    3
  • Issue
    6
  • fYear
    1992
  • fDate
    11/1/1992 12:00:00 AM
  • Firstpage
    981
  • Lastpage
    990
  • Abstract
    The representational capabilities of one-hidden-layer and two-hidden-layer nets consisting of feedforward interconnections of linear threshold units are compared. It is remarked that for certain problems two hidden layers are required, contrary to what might be in principle expected from the known approximation theorems. The differences are not based on numerical accuracy or number of units needed, nor on capabilities for feature extraction, but rather on a much more basic classification into direct and inverse problems. The former correspond to the approximation of continuous functions, while the latter are concerned with approximating one-sided inverses of continuous functions, and are often encountered in the context of inverse kinematics determination or in control questions. A general result is given showing that nonlinear control systems can be stabilized using two hidden layers, but not, in general, using just one
  • Keywords
    control system analysis; feedback; feedforward neural nets; inverse problems; nonlinear control systems; stability; feedback stabilisation; feedforward neural nets; inverse kinematics; inverse problems; linear threshold units; nonlinear control systems; stability; two-hidden-layer nets; Control systems; Control theory; Feature extraction; Kinematics; Neural networks; Neurofeedback; Nonlinear control systems; Nonlinear systems; Piecewise linear techniques; State feedback;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.165599
  • Filename
    165599