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Entropy2016,18, 110
notconsiderhere,butwhichwillbediscussed inmoredetail inupcomingwork. Forexample,one
canhaveasituationwith twolanguages inwhichaparameter isentailedbythevaluesof twoother
parameters,butentailed to twodifferentvalues in the twolanguages. In thiscase, theproposalabove
need tobemodiïŹed, because this entailedparameter should contribute to theHammingdistance
betweenthe twolanguages. Insuchasituationtheentailedparametershould increase, rather than
spoil, theefïŹciencyof thecode.Keepingentailedparameterscanbeusedforerror-correctingpurposes,
ascontributingtoerrordetection. Theroleofentailmentofparameterswasconsideredin[8], in the
useofspinglassmodels for languagechange,where theentailmentrelationsappearascouplingsat
thevertices (interaction terms)betweendifferent Ising/Pottsmodelsonthesameunderlyinggraphof
language interactions. Inupcomingwork,nowinpreparation,wewilldiscusshowtreatingdifferent
formsofentailmentofparameters in thecodingtheorysettingdescribedhererelatedto the treatment
ofentailmentrelations in thespinglassmodelof [8].
3. EntropyandComplexityforLanguageFamilies
3.1.WhytheAsymptoticBound?
In theexamplesdiscussedabovewecomparedthepositionof thecodepointassociatedtoagiven
setof languages tocertaincurves in thespaceofcodeparameters. Inparticular,we focusedonthe
asymptoticboundcurveandtheGilbertâVarshamovcurve. It shouldbepointedout that these two
curveshaveaverydifferentnature.
Theasymptoticbound is theonlycurve that separates regions in thespaceofparameters that
correspondtocodepointswithentirelydifferentbehavior.Asshownin[13,24], codepoints in thearea
belowtheasymptoticboundarerealizedwith inïŹnitemultiplicityandïŹlldensely theregion,while
codepoints that lieabovetheasymptoticboundare isolatedandrealizedwithïŹnitemultiplicity.
TheGilbertâVarshamovcurve, by contrast, is related to the statistical behavior of sufïŹciently
randomcodes (aswerecall inSection3.2below),butdoesnotseparate tworegionswithsigniïŹcantly
differentbehavior in thespaceofcodepoints. Thus, in this respect, theasymptoticboundisamore
natural curve toconsider thantheGilbertâVarshamovcurve.
Thus,aheuristic interpretationof thepositionofcodesobtainedfromgroupsof languages,with
respect to theasymptoticboundcanbeunderstoodas follows. Thepositionofacodepointaboveor
belowtheasymptoticboundreïŹectsaverydifferentbehaviorof thecorrespondingcodewithrespect
tohoweasilyâdeformableâ it is. Thesporadic codes that lieabove theasymptoticboundare rigid
objects, in contrast to thedeformable objects below the asymptotic bound. In termsofproperties
of the distribution of syntactic parameterswithin a set of languages, this different nature of the
associatedcodecanbeseenasameasureof thedegreeofâdeformabilityâof theparameterdistribution:
in languages that belong to the samehistorical linguistic families, the parameter distributionhas
evolvedhistoricallyalongwith thedevelopmentof the familyâsphylogenetic tree,andoneexpects
that correspondingly the codeparameterswill indicate a higher degree of âdeformabilityâ of the
correspondingcode. Ifagroupof languages ischosenthatbelongtoverydifferenthistorical families,
on thecontrary,oneexpects that thedistributionofsyntacticparameterswillnotnecessarily leadany
longer toacodethathas thesamekindofdeformabilityproperty: codepointsabovetheasymptotic
boundmayberealizablebythis typeof languagegroups.
There is no similar interpretation for the position of the code point with respect to the
GilbertâVarshamovline.Aninterpretationof thatpositioncanbesought in termsofShannonentropy,
aswediscussbelow. Summarizing: themainconceptualdistinctionbetweentheGilbertâVarshamov
line and the asymptotic bound is that the GV line represents only a statistical phenomenon, as
wereviewbelow,while theasymptoticboundrepresents a true separationbetween twoclassesof
structurallydifferentcodes, in thesenseexplainedabove.
448
Differential Geometrical Theory of Statistics
- Title
- Differential Geometrical Theory of Statistics
- Authors
- Frédéric Barbaresco
- Frank Nielsen
- Editor
- MDPI
- Location
- Basel
- Date
- 2017
- Language
- English
- License
- CC BY-NC-ND 4.0
- ISBN
- 978-3-03842-425-3
- Size
- 17.0 x 24.4 cm
- Pages
- 476
- Keywords
- Entropy, Coding Theory, Maximum entropy, Information geometry, Computational Information Geometry, Hessian Geometry, Divergence Geometry, Information topology, Cohomology, Shape Space, Statistical physics, Thermodynamics
- Categories
- Naturwissenschaften Physik