Estimating the Number of Sinusoids and its Performance Analysis

Abstract

Detecting the number of signals and estimating the parameters of the signals is an important problem in signal processing. Quite a number of papers appeared in the last twenty years regarding the estimation of the parameters of the sinusoidal components but not that much of attention has been given in estimating the number of terms presents in a sinusoidal signal. Fuchs developed a criterion based on the perturbation analysis of the data auto correlation matrix to estimate the number of sinusoids, which is in some sense a subjective-based method. Recently Reddy and Biradar proposed two criteria based on AIC and MDL and developed an analytical framework for analyzing the performance of these criteria. In this paper we develop a method using the extended order modelling and singular value decomposition technique similar to that of Reddy and Biradar. We use penalty function technique but instead of using any fixed penalty function like AIC or MAL, a class of penalty functions satisfying some special properties has been used.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1997
Accession Number
ADA332777

Entities

People

  • Debasis Kundu

Organizations

  • Pennsylvania State University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Computational Science
  • Consistency
  • Data Science
  • Decomposition
  • Eigenvalues
  • Information Processing
  • Information Science
  • Mathematics
  • Monte Carlo Method
  • Perturbations
  • Probability
  • Random Variables
  • Signal Processing
  • Simulations
  • Statistics
  • United States Government

Fields of Study

  • Engineering

Readers

  • Statistical inference.