Parameterization of nonideal quantizers for simultaneous estimation of quantizer and excitation signal parameters

Tamás Virosztek, I. Kollár

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper deals with the estimation of signal and quantizer parameters based on a nonideally sampled and quantized measurement record. It proposes solutions to reduce the inherently high-dimensional parameter space via approximation of the quantizer nonideality to make the computation possible in PC/MATLAB environment. The performance of the approximation techniques is examined as well. The computational demand of the proposed approximate maximum likelihood (AML) estimators is investigated and compared to the computational demand of the maximum likelihood (ML) estimators without approximation.

Original languageEnglish
Pages (from-to)412-419
Number of pages8
JournalMeasurement: Journal of the International Measurement Confederation
Volume111
DOIs
Publication statusPublished - Dec 1 2017

Fingerprint

Simultaneous Estimation
Parameterization
parameterization
Maximum likelihood
counters
Excitation
estimators
Maximum Likelihood Estimator
demand
Approximation
approximation
PC
MATLAB
excitation
Parameter Space
High-dimensional
performance
Demand

Keywords

  • ADC testing
  • Approximation
  • Maximum likelihood
  • Nonideal quantizers
  • Parameter estimation
  • Quantization

ASJC Scopus subject areas

  • Statistics and Probability
  • Education
  • Condensed Matter Physics
  • Applied Mathematics

Cite this

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