ESTIMATION OF SIGNAL PARAMETERS USING QUANTIZED OBSERVATIONS.

Chung Chieh Lee*

*Corresponding author for this work

Research output: Contribution to conferencePaper

Abstract

This paper considers estimation of signal parameters from a sequence of independent, identically distributed, and quantized observations. The approach is based on discrete statistical modeling of random processes and channel statistics. Three best asymptotically normal (BAN) estimates are discussed. The maximum likelihood (ML) estimate of a constant signal in additive white Laplace noise is derived. Then, for small signal parameters, a Locally Efficient (LE) estimator is developed. This estimator, as an approximation to the ML estimator, is simple and nonparametric, and is shown to be unbiased, consistent, asymptotically normal, and efficient in the limit when the signal parameter vanishes.

Original languageEnglish (US)
Pages546-551
Number of pages6
StatePublished - Dec 1 1982

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Maximum likelihood
Random processes
Statistics

ASJC Scopus subject areas

  • Engineering(all)

Cite this

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abstract = "This paper considers estimation of signal parameters from a sequence of independent, identically distributed, and quantized observations. The approach is based on discrete statistical modeling of random processes and channel statistics. Three best asymptotically normal (BAN) estimates are discussed. The maximum likelihood (ML) estimate of a constant signal in additive white Laplace noise is derived. Then, for small signal parameters, a Locally Efficient (LE) estimator is developed. This estimator, as an approximation to the ML estimator, is simple and nonparametric, and is shown to be unbiased, consistent, asymptotically normal, and efficient in the limit when the signal parameter vanishes.",
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ESTIMATION OF SIGNAL PARAMETERS USING QUANTIZED OBSERVATIONS. / Lee, Chung Chieh.

1982. 546-551.

Research output: Contribution to conferencePaper

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