Accession Number : ADA193532
Title : Adaptive Identification by Systolic Arrays.
Descriptive Note : Master's thesis,
Corporate Author : NAVAL POSTGRADUATE SCHOOL MONTEREY CA
Personal Author(s) : Willis, Paul A
PDF Url : ADA193532
Report Date : Dec 1987
Pagination or Media Count : 69
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.
Descriptors : *ALGORITHMS, *ADAPTIVE CONTROL SYSTEMS, ADAPTIVE SYSTEMS, ARITHMETIC, COMPUTER ARCHITECTURE, DECOMPOSITION, EFFICIENCY, EQUATIONS, IDENTIFICATION, INPUT, LEAST SQUARES METHOD, METHODOLOGY, NUMERICAL ANALYSIS, OUTPUT, PARALLEL PROCESSING, RECURSIVE FUNCTIONS, SAMPLING, THESES, FLOATING POINT OPERATION, INTEGRATED CIRCUITS
Subject Categories : Operations Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE