Persistent Link:
http://hdl.handle.net/10150/609805
Title:
Optimum Quantization for Minimum Distortion
Author:
Caprio, James R.; Westin, Nancy; Esposito, John
Affiliation:
Comptek Research, Inc.; State University of N.Y. at Buffalo
Issue Date:
1978-11
Rights:
Copyright © International Foundation for Telemetering
Collection Information:
Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
Publisher:
International Foundation for Telemetering
Journal:
International Telemetering Conference Proceedings
Abstract:
This paper treats the problem of optimal selection of data quantization levels for minimum error. No assumptions are made regarding the underlying statistics of the process to be quantized. A finite precursor sample of the data is analyzed to infer the underlying distribution. Selection of optimum quantization levels can then be related to the generation of an optimum histogram for the data record. The optimum histogram is obtained by a dynamic programming approach for both least mean square error and minimum Chebychev error criteria. Transmitted data can then be quantized according to levels specified by the histogram. The process can be repeated periodically either with a new data sample, if the underlying process is nonstationary, or performed on the accumulated record in the stationary case.
Sponsors:
International Foundation for Telemetering
ISSN:
0884-5123; 0074-9079
Additional Links:
http://www.telemetry.org/

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleOptimum Quantization for Minimum Distortionen_US
dc.contributor.authorCaprio, James R.en
dc.contributor.authorWestin, Nancyen
dc.contributor.authorEsposito, Johnen
dc.contributor.departmentComptek Research, Inc.en
dc.contributor.departmentState University of N.Y. at Buffaloen
dc.date.issued1978-11-
dc.rightsCopyright © International Foundation for Telemeteringen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.en
dc.publisherInternational Foundation for Telemeteringen
dc.description.abstractThis paper treats the problem of optimal selection of data quantization levels for minimum error. No assumptions are made regarding the underlying statistics of the process to be quantized. A finite precursor sample of the data is analyzed to infer the underlying distribution. Selection of optimum quantization levels can then be related to the generation of an optimum histogram for the data record. The optimum histogram is obtained by a dynamic programming approach for both least mean square error and minimum Chebychev error criteria. Transmitted data can then be quantized according to levels specified by the histogram. The process can be repeated periodically either with a new data sample, if the underlying process is nonstationary, or performed on the accumulated record in the stationary case.en
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.identifier.issn0884-5123-
dc.identifier.issn0074-9079-
dc.identifier.urihttp://hdl.handle.net/10150/609805-
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.typetexten
dc.typeProceedingsen
dc.relation.urlhttp://www.telemetry.org/en
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