AR Parameter Estimation Using TMS320C30 Digital Signal Processor Chip.

Abstract

Autoregressive analysis is used in modern signal processing applications for modeling and estimation of random signals. High speed digital signal processors with advanced architecture and special digital signal processing instructions, mostly compiled in C language, can be used in these applications to achieve realtime performance. A commercially available digital signal processor has been used in this work to estimate the AR parameters and power spectral density from the given input data by using the Levinson, Burg and Schur algorithms. This work produced a library file that contains the object files of the AR parameter estimation algorithms. The time required in terms of the cycle counts to execute each algorithm is listed for different data lengths and model orders.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1995
Accession Number
ADA305733

Entities

People

  • Mucahit Karasu

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Assembly Languages
  • Central Processing Units
  • Computer Programs
  • Computers
  • Computing System Architectures
  • Data Transmission
  • Digital Signal Processing
  • Electrical Engineering
  • Engineering
  • Instruction Set Architecture
  • Instructions
  • Language
  • Large Scale Integration
  • Serial Ports
  • Signal Processing
  • Very Large Scale Integration

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Statistical inference.