Adaptive Identification by Systolic Arrays.

Abstract

This thesis is concerned with the implementation of an adaptive identification algorithm using parallel processing and systolic arrays. In particular, discrete samples of input and output data of a system with uncertain characteristics are used to determine the parameters of its model. The identification algorithm is based on recursive least squares, QR decomposition, and block processing techniques with covariance resetting. Along similar lines as previous approaches, the identification process is based on the use fo Givens rotations. This approach uses the Cordic algorithm for improved numerical efficiency in performing the rotations. Additionally, floating point and fixed point arithmetic implementations are compared. Keywords: Theses; Very large scale integrated circuits; Equations; Recursive cast squares.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1987
Accession Number
ADA193532

Entities

People

  • Paul A. Willis

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Arithmetic
  • Computer Science
  • Computers
  • Control Systems
  • Covariance
  • Decomposition
  • Engineering
  • Equations
  • Floating Point Operations
  • Linear Arrays
  • Linear Systems
  • Parallel Computing
  • Parallel Processing
  • Schools
  • Simulations
  • United States

Fields of Study

  • Engineering

Readers

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