Accession Number : ADA305733

Title :   AR Parameter Estimation Using TMS320C30 Digital Signal Processor Chip.

Descriptive Note : Master's thesis,

Corporate Author : NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s) : Karasu, Mucahit

PDF Url : ADA305733

Report Date : DEC 1995

Pagination or Media Count : 110

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.

Descriptors :   *SIGNAL PROCESSING, *REAL TIME, *CHIPS(ELECTRONICS), *REGRESSION ANALYSIS, *MICROCOMPUTERS, FILES(RECORDS), ALGORITHMS, INPUT, DIGITAL SYSTEMS, DENSITY, PARAMETERS, PROGRAMMING LANGUAGES, COUNTING METHODS, THESES, POWER SPECTRA, CYCLES, ESTIMATES, LENGTH, SIGNALS, ARCHITECTURE, C PROGRAMMING LANGUAGE.

Subject Categories : Electrical and Electronic Equipment
      Numerical Mathematics
      Computer Programming and Software

Distribution Statement : APPROVED FOR PUBLIC RELEASE