RANDOM SIGNAL FREQUENCY IDENTIFICATION BASED ON AR MODEL SPECTRAL ESTIMATION

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic

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VOLUME 9 , ISSUE 2 (June 2016) > List of articles

RANDOM SIGNAL FREQUENCY IDENTIFICATION BASED ON AR MODEL SPECTRAL ESTIMATION

Chunhuan Song *

Keywords : AR model, power spectral estimation, Burg algorithm.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 9, Issue 2, Pages 884-908, DOI: https://doi.org/10.21307/ijssis-2017-900

License : (CC BY-NC-ND 4.0)

Received Date : 06-January-2016 / Accepted: 22-March-2016 / Published Online: 01-June-2016

ARTICLE

ABSTRACT

The power spectral estimation is an important element in the random signal analysis. The
paper will introduce the principles of the classical power spectral estimation and modern power spectral
estimation, analyses their characteristics and application in MATLAB simulation. The variance obtained
by the classical power spectral estimation is inversely proportional to its resolution, the resolution of the
modern spectral estimation are not subject to this restriction, but also the variance achieve greatly
improvement, which is a great importance for improving the accuracy of the power spectral estimation.
This paper mainly studies AR model of parametric modeling in the modern spectral estimation, and then
uses the simulation between the classical power spectral estimation and modern power spectral
estimation for comparison, verifies the analysis of the modern power spectral estimation based on
ARmodel is more accurate than the classical power spectral estimation.

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