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Mathematical Theory of Uniformity and its Applications in Ecology and Chaos (SpringerBriefs in Applied Sciences and Technology) PDF

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Preview Mathematical Theory of Uniformity and its Applications in Ecology and Chaos (SpringerBriefs in Applied Sciences and Technology)

SpringerBriefs in Applied Sciences and Technology Mathematical Methods SeriesEditors AnnaMarciniak-Czochra,InstituteofAppliedMathematics,IWR,Universityof Heidelberg,Heidelberg,Germany ThomasReichelt,Emmy-NoetherResearchGroup,UniversitätHeidelberg, Heidelberg,Germany MathematicalMethodsisanewseriesofSpringerBriefsdevotedtonon-standardand freshmathematicalapproachestoproblemsinappliedsciences.Compactvolumes of50to125pages,eachpresentingaconcisesummaryofamathematicaltheory,and providinganovelapplicationinnaturalsciences,humanitiesorotherfieldsofmathe- matics.Theseriesisintendedforappliedscientistsandmathematicianssearchingfor innovative mathematical methods to address problems arising in modern research. Examples of such topics include: algebraic topology applied in medical image processing, stochastic semigroups applied in genetics, or measure theory applied indifferentialequations. · Chuanwen Luo Chuncheng Wang Mathematical Theory of Uniformity and its Applications in Ecology and Chaos ChuanwenLuo ChunchengWang CenterofUniformityTheory DepartmentofMathematics andApplication HarbinInstituteofTechnology NortheastForestryUniversity Harbin,Heilongjiang,China Harbin,Heilongjiang,China ISSN 2191-530X ISSN 2191-5318 (electronic) SpringerBriefsinAppliedSciencesandTechnology ISSN 2365-0826 ISSN 2365-0834 (electronic) SpringerBriefsinMathematicalMethods ISBN 978-981-19-5511-2 ISBN 978-981-19-5512-9 (eBook) https://doi.org/10.1007/978-981-19-5512-9 ©TheAuthor(s),underexclusivelicensetoSpringerNatureSingaporePteLtd.2022 Thisworkissubjecttocopyright.AllrightsaresolelyandexclusivelylicensedbythePublisher,whether thewholeorpartofthematerialisconcerned,specificallytherightsoftranslation,reprinting,reuse ofillustrations,recitation,broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,and transmissionorinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilar ordissimilarmethodologynowknownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthors,andtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor theeditorsgiveawarranty,expressedorimplied,withrespecttothematerialcontainedhereinorforany errorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregardtojurisdictional claimsinpublishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSingaporePteLtd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore Preface Thedistributionofafinitenumberofpointsinapolyhedronisreferredtoasapattern inthisbook.Thedegreeofuniformityofplantsdistributedinapolygonalareahas been studied for more than a century. The mathematical problem behind this is to measuretherandomnessofasetofdiscretepoints.Theuniformdegree,introduced inthisbook,summarizesthecorrelatedresultsintheliterature,unifiestheirmethods, andsimplifiestheprocessofsampling,computationandtesting.Moreimportantly, the extent of randomness and chaos is also put together within the framework of uniformdegree. The randomness called the external stochasticity and chaos called the internal stochasticityhavelongbeenseparated,andconsideredtobelongtodifferentsubjects. The reason behind this is the lack of theory and method, that can unify these two concepts.Thestandpointinthisbook,basedonthemeasurementofuniformdegree forthechaotictimeseries,isinclinedtoadmitthatthereisnosubstantialdifference betweenrandomnessandchaos.Auniformdegreeisanindexthatcanmeasureboth stochasticandchaotictimeseries.Thetheoryofuniformityisestablishedbasedon theconceptofuniformdegree. The uniform degree of the pattern generated by a distribution function F in a polyhedronisabbreviatedastheuniformdegreeofadistributionfunction,denoted byL ,andtheuniformdegreeofauniformdistributionfunctionisdenotedbyL . F U TheuniformdegreeisanalogoustotheconceptofShannon’sentropy.Itisconjectured that the uniform degree of a uniform distribution function is greater than those of all the other distribution functions, that is, “a uniform distribution function is the mostuniform”,or L ≤ L .Thisconjecturewillexplainwhytheuniformdegree F U of a chaotic orbit must lie in [0, L ], since the uniform degree L is the critical U U situationthatachaoticorbitcanneverattain.Manynumericalillustrationsshowthat theuniformdegreeexhibitsbetterresultsthantheotherindexesformeasuringchaos. BasedontheMonteCarlomethod,anypatternobeyingadistributionfunction F inapolyhedroncanbeviewedasthetransformationF−1ofthepatterngeneratedby auniformdistributionfunction.RecallthatthenonlinearityofFisinlinewiththatof F−1.NumericalillustrationsshowthatthenonlinearityofFisinverselyproportional toL ,thatis,thenonlineartransformationofapatternwillreduceitsuniformdegree, F v vi Preface andtheuniformdegreeofapatternwillnotchangeunderatransformationonlyif F islinear.Recallthatonlytheuniformdistributionfunctionislinear.Toacertain extent,thisimpliestheconjectureistrue.Thisalsoseemstobeconnectedwiththe processofformationofadissipativestructure. Inaword,itseemsthatorderedandunordered,periodicandchaotic,deterministic and stochastic, aggregate and uniform patterns can be unified in the framework of uniformdegree. As illustrations, k-step chaometry, which is equivalent to a uniform degree, is usedtoexaminetheinternalfaultsintransformers,basedonthetimeseriescaused byvibration.Otherexamplesinvolvethetestofelectrocardiogramsandelectroen- cephalograms, and the theory of uniformity may also have wide applications in practice. Turbulenceisanintricatepatterninaboundedarea(suchasagivenpolyhedron), whichcanbedescribedbythemulti-dimensionaluniformdegree.Itisworthtrying forscholars,whohavethedataonturbulence. Inamaterialcomposition,theparticleswillbecomeuniforminthemediumafter agitating,andauniformdegreecanmeasuretheuniformityofparticlesinthisprocess. Thetheoryofuniformityisamathematicaltheoryontheuniformdegree,andit hasmanyapplicationsinvariousfields.Nevertheless,thetheoryisstilldeveloping andisfarfromcomplete. Harbin,China ChuanwenLuo ChunchengWang Contents 1 UniformDegree ................................................. 1 1.1 Introduction ................................................ 1 1.2 UniformDegree ............................................. 2 1.3 ContainedUniformDegreeTheorem ........................... 4 1.4 UniformDegreeTheoremforn-dimRandomPattern ............. 11 1.5 UniformDegreeandEntropy .................................. 17 1.6 NumericalTestfortheConjecture ............................. 21 1.7 ApplicationsofUniformDegreeTheoremsinPlantPattern TypeTest ................................................... 31 1.8 UniversalityofUniformityMeasurement ....................... 33 References ...................................................... 52 2 AnInterpretationofChaosbyUniformDegree .................... 55 2.1 Introduction ................................................ 55 2.2 InstantaneousChaometryandk-StepChaometry ................. 55 2.3 InstantaneousChaometryandUniformDegree .................. 61 2.4 MoreApplicationsofk-StepChaometry ........................ 63 2.5 Applicationof250-StepChaometryinHeartRateProblem ........ 65 2.6 K-StepChaometryinVibrationFaultDetection .................. 67 References ...................................................... 69 3 Simulationsonk-StepChaometry ................................ 71 3.1 Introduction ................................................ 71 3.2 LorenzSystem .............................................. 72 3.3 ApplicationofInstantaneousChaometry ........................ 78 3.4 ICM forLargek ............................................ 81 4 ApplicationsofUniformDegreeinForestryandEcology ............ 85 4.1 EcologicalPattern ........................................... 85 4.2 MonopolizedDiskandUniformDegree ........................ 87 vii viii Contents √ 4.3 ApplicationsofUniformDegree—TheRuleof 2 ............... 88 4.3.1 MonopolizedDiskandUniformDegree .................. 90 4.3.2 DiversityofDistance .................................. 92 References ...................................................... 93 Chapter 1 Uniform Degree 1.1 Introduction Thedistributionofafinitenumberofpointsinapolygonisreferredtoasapattern in this book. Aggregation and uniformity are two typical opposite features of a pattern.Basedontheuniformdegreedefinedinthiscontext,apatternwithuniform degree zero, like a periodic orbit, is the most aggregate pattern and the uniform degree of any chaotic orbit must be greater than 0. For any segment of a chaotic orbit,itmaybehaveineitheranaggregateorauniformway.However,itsaverage uniform degree is invariant, which is the reason for measuring chaotic behaviour by the uniform degree. Based on this, the word “chaometry” has been invented, meaning the measurement of chaos. The uniform degree of the pattern generated byadistributionfunction F inapolygonisabbreviatedastheuniformdegreeofa distributionfunction,denotedby L . F TheuniformdegreeofauniformdistributionfunctionisdenotedbyL ,andthe U uniformdegreeofthepatterngeneratedbyachaoticorbitvariesfrom0to L . U TheuniformdegreeisanalogoustotheconceptofShannon’sentropy.Itiscon- jectured that the uniform degree of a uniform distribution function is greater than thoseofalltheotherdistributionfunctions,thatis,theuniformdistributionfunction isthemostuniform,orL ≤ L .Thisconjecturewillexplainthatwhytheuniform F U degree of a chaotic orbit must lie in [0, L ], since the uniform degree L is the U U criticalsituationthatachaoticorbitcanneverattain.Manynumericalillustrations showthatuniformdegreeperformbetterthantheotherindexesformeasuringchaos. Based on the Monte Carlo method, any complex pattern obeying a distribution function F in a bounded area can be viewed as the nonlinear transformation F−1 ofthepatterngeneratedbyauniformdistributionfunction,anditsfeaturescanbe characterizedbytheuniformdegree. Turbulenceisanintricatepatterninaboundedarea(suchasagivenpolyhedron), whichcanbedescribedbythemulti-dimensionaluniformdegree.Itisworthtrying forscholars,whohavedataonturbulence. ©TheAuthor(s),underexclusivelicensetoSpringerNatureSingaporePteLtd.2022 1 C.LuoandC.Wang,MathematicalTheoryofUniformityanditsApplicationsinEcology andChaos,SpringerBriefsinMathematicalMethods, https://doi.org/10.1007/978-981-19-5512-9_1

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