Optimum Quantization for Local Decision Based on Independent Samples

H. Vincent Poor; J. B. Thomas

doi:10.1016/0016-0032(77)90133-8

Optimum Quantization for Local Decision Based on Independent Samples

H. Vincent Poor, J. B. Thomas

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

The problem of designing quantizers for use in decision-making systems is considered. Applying the theory of local tests, general criteria are derived for the optimal selection of quantizer parameters for the large-sample-size case. These criteria agree with previously established results based on optimization in terms of distance measures and are shown also to lead to that quantizer-decision system which is most efficient asymptotically. To illustrate the design procedure, several applications to signal detection are discussed.

Original language	English (US)
Pages (from-to)	549-561
Number of pages	13
Journal	Journal of the Franklin Institute
Volume	303
Issue number	6
DOIs	https://doi.org/10.1016/0016-0032(77)90133-8
State	Published - Jun 1977

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Signal Processing
Computer Networks and Communications
Applied Mathematics

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10.1016/0016-0032(77)90133-8

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abstract = "The problem of designing quantizers for use in decision-making systems is considered. Applying the theory of local tests, general criteria are derived for the optimal selection of quantizer parameters for the large-sample-size case. These criteria agree with previously established results based on optimization in terms of distance measures and are shown also to lead to that quantizer-decision system which is most efficient asymptotically. To illustrate the design procedure, several applications to signal detection are discussed.",

author = "Poor, {H. Vincent} and Thomas, {J. B.}",

note = "Funding Information: *This research was supported by the National Science Foundation under Grant ENG76-19808 and by the U.S. Army Research Office under Grant DAAG29-75-G-0192.",

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N2 - The problem of designing quantizers for use in decision-making systems is considered. Applying the theory of local tests, general criteria are derived for the optimal selection of quantizer parameters for the large-sample-size case. These criteria agree with previously established results based on optimization in terms of distance measures and are shown also to lead to that quantizer-decision system which is most efficient asymptotically. To illustrate the design procedure, several applications to signal detection are discussed.

AB - The problem of designing quantizers for use in decision-making systems is considered. Applying the theory of local tests, general criteria are derived for the optimal selection of quantizer parameters for the large-sample-size case. These criteria agree with previously established results based on optimization in terms of distance measures and are shown also to lead to that quantizer-decision system which is most efficient asymptotically. To illustrate the design procedure, several applications to signal detection are discussed.

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Optimum Quantization for Local Decision Based on Independent Samples

Abstract

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