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Information Theory Applied to Animal Communication Systems and Its Possible Application to SETI

Published online by Cambridge University Press:  19 September 2017

Sean F. Hanser ,
Laurance R. Doyle ,
Brenda McCowan  and
Jon M. Jenkins
Sean F. Hanser
Affiliation:
Ecology Graduate Group, University of California, One Shields Avenue, Davis, CA 95616 USA
Laurance R. Doyle
Affiliation:
SETI Institute, 2035 Landings Drive, Mountain View, CA 94043 USA
Brenda McCowan
Affiliation:
School of Veterinary Medicine: Population Health and Reproduction, University of California, Davis, 18830 Road 112, Tulare, CA 93274, USA
Jon M. Jenkins
Affiliation:
SETI Institute, NASA Ames Research Center 245–3, Moffet Field, CA 94035 USA

Abstract

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Information theory, as first introduced by Claude Shannon (Shannon & Weaver 1949) quantitatively evaluates the organizational complexity of communication systems. At the same time George Zipf was examining linguistic structure in a way that was mathematically similar to the components of the Shannon first-order entropy (Zipf 1949). Both Shannon's and Zipf's mathematical procedures have been applied to animal communication and recently have been providing insightful results. The Zipf plot is a useful tool for a first estimate of the characterization of a communication system's complexity (which can later be examined for complex structure at deeper levels using Shannon entropic analysis). In this paper we shall discuss some of the applications and pitfalls of using the Zipf distribution as a preliminary evaluator of the communication complexity of a signaling system.

Type
Post SETI
Information
Symposium - International Astronomical Union , Volume 213: Bioastronomy 2002: Life Among the stars , 2004 , pp. 514 - 518
Copyright
Copyright © Astronomical Society of the Pacific 2004 

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