Efficient Multichannel Autoregressive Modeling in Time and Frequency Domain.

Abstract

The single channel autoregressive lattice has been successfully applied to problems including speech analysis and recognition, spectral analysis and noise cancelling. More recently the two channel autoregressive (AR) lattice has been exploited for autoregressive moving average (ARMA) analysis of systems for modeling and identification. This dissertation considers the multichannel AR lattice when applied to ARMA systems analysis. Constraints on lattice parameters, based on the input output relations of the system under test, are developed. The lattice is redefined in terms of the frequency domain representation of the input data. This proves to be useful because it allows the input to be normalized so that the lattice yields a consistant set of parameters independent of the test source characteristics. Lastly the lattice is redefined in terms of correlations of the input signals. This results in a computationally and storage efficient lattice algorithm. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1982
Accession Number
ADA115752

Entities

People

  • David J. Klich

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Computer Science
  • Cross Correlation
  • Electrical Engineering
  • Engineering
  • Equations
  • Frequency
  • Frequency Domain
  • Identification
  • Linear Systems
  • Operating Systems
  • Plants
  • Simulations
  • Speech Analysis
  • Systems Analysis
  • Theses

Fields of Study

  • Engineering

Readers

  • Speech Processing/Speech Recognition.
  • Statistical inference.