ADAPTIVE NONLINEAR MODELING WITH QUANTIZERS.

Abstract

Identification of the dynamics of a nonlinear plant was studied using the combination of a generalized, or equation-error, modeler with multilevel quantizing for piecewise-linear modeling. Algorithms for adapting the quantizing boundary locations and the modeling weights are derived. Conditions are established which allow converting a 'least mean square' error-correcting training algorithm for the modeling weights to a modified forced-learning algorithm which converges as rapidly as the signal statistics permit. Experimental results indicate that this type of modeler converges more rapidly than the ordinary types of nonlinear modelers, and to a more accurate solution. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jun 06, 1969
Accession Number
AD0688194

Entities

People

  • Frederic D. Powell

Organizations

  • Bell Aircraft Corporation

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Boundaries
  • Data Science
  • Dynamics
  • Equations
  • Identification
  • Information Science
  • Learning
  • Mathematics
  • Statistics
  • Training

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Programming and Software Development.