Event Compression Using Recursive Least Squares Signal Processing.

Abstract

This work presents a technique for time compressing the events in a multiple event signal using a recursive least squares adaptive linear prediction algorithm. Two event compressed signals are extracted from the update equations for the predictor; one based on the prediction error and the other on the changes in the prediction coefficients as the data is processed. Using synthetic data containing three all-pole events, experiments are performed to illustrate the performance of the two signals derived from the prediction algorithm. These experiments examine the effects of initialization, white gaussian noise, interevent interference, filtering and decimation on the compressed events contained in the two signals. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1980
Accession Number
ADA089785

Entities

People

  • Webster Pope Dove

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Covariance
  • Data Science
  • Electrical Engineering
  • Engineering
  • Equations
  • Filters
  • Filtration
  • Gaussian Noise
  • Information Processing
  • Information Science
  • Linear Filtering
  • Mathematical Filters
  • Noise
  • Signal Processing
  • Statistical Algorithms
  • Statistics

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Seismology