LEADER 09160nam 2200625 a 450 001 9910968475403321 005 20251117090917.0 010 $a1-62100-148-2 035 $a(CKB)2550000000046891 035 $a(OCoLC)750173571 035 $a(CaPaEBR)ebrary10686311 035 $a(SSID)ssj0000568791 035 $a(PQKBManifestationID)12243376 035 $a(PQKBTitleCode)TC0000568791 035 $a(PQKBWorkID)10536649 035 $a(PQKB)11410141 035 $a(MiAaPQ)EBC3021987 035 $a(Au-PeEL)EBL3021987 035 $a(CaPaEBR)ebr10686311 035 $a(BIP)44323256 035 $a(BIP)31882102 035 $a(EXLCZ)992550000000046891 100 $a20100813d2011 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 00$aCellular automata /$fThomas M. Li, editor 205 $a1st ed. 210 $aNew York $cNova Science Publishers, Inc.$dc2011 215 $a1 online resource (309 p.) 225 1 $aMathematics research developments 225 1 $aComputer science, technology and applications 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a1-61761-592-7 320 $aIncludes bibliographical references and index. 327 $aIntro -- CELLULAR AUTOMATA -- CELLULAR AUTOMATA -- CONTENTS -- PREFACE -- Chapter 1 CA UPGRADING FOR EXTENDING THE OPTIMIZATION PROBLEM SOLVING ABILITY -- ABSTRACT -- 1. INTRODUCTION -- How Can We Guide the System by CA? -- 2. COMPLEX SYSTEMS -- 3. OPTIMIZATION -- 3.1. History -- 3.2. Objective Function -- 3.3. System Optimization -- 4. OPTIMIZATION BY CA -- 4.1. Optimization by CA+SA -- 4.1.1. Simulated annealing -- 4.1.2. Procedure -- 4.1.3. A Sample problem solving -- 4.2. Optimization by CA -- 4.2.1. Procedure -- 4.2.2. A Sample problem solving -- 5. CONCLUSION -- REFERENCES -- Chapter 2 MODELING DRUG RELEASE USING CELLULAR AUTOMATA: EVOLUTION AND TRENDS IN PHARMACEUTICAL SCIENCES -- ABSTRACT -- 1. INTRODUCTION -- 2. HISTORICAL REVIEW -- 3. MODELING MATRIX EROSION -- 3.1. Describing the Primary State of the Matrix -- 3.2. Step 1 of Polymer Erosion: Water Penetration in the Matrix -- 3.3. Step 2 of Polymer Erosion: Polymer Degradation -- 3.4. Step 3 of Polymer Erosion: Loss of Polymer Bulk -- 4. MODELING DRUG DIFFUSION -- 5. EVALUATING THE PREDICTIVE VALUE OF MODELS -- 6. CONCLUSION -- REFERENCES -- Chapter 3 A MODEL OF CELLULAR AUTOMATA FOR THE SPATIAL ANALYSIS OF APHIDS AND LADYBUGS -- ABSTRACT -- 1. PRELIMINARIES -- 1.1. Citrus Sudden Death -- 1.2. Cellular Automata -- 1.3. Fuzzy Rule-Based System -- 2. CELLULAR AUTOMATA MODEL -- 3. SIMULATIONS WITH CELLULAR AUTOMATA MODEL -- CONCLUSIONS -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 4 CELLULAR AUTOMATA OPTIMIZATION VIA EVOLUTIONARY METHODS -- ABSTRACT -- INTRODUCTION -- CELLULAR FORMULATION -- COMBINED CELLULAR - GENETIC FORMULATION -- LOCAL SEARCH ALGORITHM -- RESULTS AND DISCUSSION -- REFERENCES -- Chapter 5 PARALLEL CELLULAR AUTOMATA ON CHIP -- ABSTRACT -- 1. INTRODUCTION -- 2. A SIMPLE CELLULAR AUTOMATON -- 3. RECONFIGURABLE COMPUTING -- 4. CELLULAR AUTOMATA RECONFIGURABLE PROCESSOR. 327 $a4.1. Modeling of the Algorithm -- 4.2. Processor Design -- 4.3. Hardware Implementation -- 5. EXPERIMENTAL RESULTS -- 6. CONCLUSIONS AND FUTURE WORK -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter6 EVOLVINGCELLULARAUTOMATAFORFORMGENERATIONINARTIFICIALDEVELOPMENT -- Abstract -- 1.Introduction -- 2.CellularGrowthTestbed -- 2.1.2DNeighborhoods -- 2.1.1.VonNeumannNeighborhood -- 2.1.2.MooreNeighborhood -- 2.1.3.2-RadialNeighborhood -- 2.1.4.MargolusNeighborhood -- 2.2.3DNeighborhood -- 2.3.NetLogoModels -- 3.MorphogeneticGradients -- 4.Genomes -- 5.GeneticAlgorithm -- 5.1.Chromosomestructure -- 5.1.1.Chromosomestructureforformgeneration -- 5.1.2.Chromosomestructureforpatterngeneration -- 5.2.Fitnessfunction -- 5.2.1.Onestructuralgene -- 5.2.2.Multiplestructuralgenes -- 6.FormGeneration -- 6.1.2Dshapes -- 6.2.3Dshapes -- 6.3.Chosenneighborhoodsforpatterngeneration -- 7.PatternGeneration -- 8.Discussion -- 9.Conclusion -- References -- Chapter7 STRUCTURALANDSYMMETRYANALYSISOFDISCRETEDYNAMICALSYSTEMS -- Abstract -- 1.Introduction -- 2.DiscreteDynamics -- 2.1.DiscreteDynamicalModelswithSpace -- 2.1.1.ExampleofDiscreteModelwithEmergentSpace-time. -- 2.1.2.SpaceSymmetriesinMoreDetail. -- 2.1.3.UnificationofSpaceandInternalSymmetries. -- 3.StructuralAnalysisofDiscreteRelations -- 3.1.BasicDefinitionsandConstructions -- 3.1.1.Relations -- 3.1.2.CompatibilityofSystemsofRelations -- 3.1.3.DecompositionofRelations -- 3.1.4.OnRepresentationofRelationsinComputer -- 3.2.Illustration:ApplicationtoSomeCellularAutomata -- 3.2.1.J.Conway'sGameofLife -- 3.2.2.ElementaryCellularAutomata -- 4.Soliton-likeStructuresinDeterministicDynamics -- CommentsonReversibilityinDiscreteSystems. -- 5.MesoscopicLatticeModels -- 5.1.StatisticalMechanics -- 5.2.Mesoscopy -- 5.2.1.LatticeModels. -- 5.3.PhaseTransitions -- 6.GaugeConnectionandQuantization -- 6.1.DiscreteGaugePrinciple. 327 $a6.2.QuantumBehaviorandGaugeConnection -- 6.2.1.IllustrativeExampleInspiredbyFreeParticle. -- 6.2.2.LocalQuantumModelsonRegularGraphs -- 6.3.GeneralDiscussionofQuantizationinFiniteSystems -- 6.3.1.PermutationsandLinearRepresentations -- 6.3.2.InterpretationofQuantumDescriptioninFiniteBackground -- 7.Conclusion -- Acknowledgments -- References -- Chapter8 REVERSIBILITYOFCELLULARAUTOMATA -- Abstract -- 1.Introduction -- 2.Quivers -- 2.1.DeBruijnQuiver -- 2.2.AdjacencyMatrices -- 3.CellularAutomata -- 3.1.WolframCellularAutomaton -- 3.2.CorrespondencetodeBruijnQuiver -- 3.3.GlobalTransitionofConfigurationAlgebra -- 3.4.TransitionMatrices -- 4.ReversibilityofCellularAutomata -- 4.1.PeriodicReductionsofWCA -- 4.2.Reversibilityofn-WCA -- 4.3.NecessaryConditionsforReversibilityofn-WCA -- 5.ReversibleRulesinECA -- 5.1.EquivalenceClassesofRules -- 5.2.ReversibilityofRule154 -- 5.3.CompleteListofReversibleRules -- 6.Conclusion -- REFERENCES -- Chapter9 FROMGLIDERSTOUNIVERSALITYOFCELLULARAUTOMATA:ANOTHER2D2-STATEUNIVERSALAUTOMATON -- Abstract -- 1.Introduction -- 2.FormalisationsandNotations -- 2.1.SetofCellularAutomata -- 2.2.EvolutionofCellularAutomata -- 2.3.Isotropy -- 2.4.NumberofAutomata -- 2.5.QuiescentState -- 2.6.Patterns -- 2.6.1.Definition -- 2.6.2.Glider -- 2.7.GliderGun -- 3.GameofLife -- 3.1.TransitionRule -- 3.2.ANDGate -- 3.3.NOTGate -- 4.Gliders -- 4.1.EvolutionaryAlgorithm -- 4.2.Result -- 4.2.1.OrthogonalGliders -- 4.2.2.DiagonalGliders -- 5.Universality -- 5.1.TheR0Automaton:anExperimentalResult -- 5.2.Lookingforan"Eater" -- 5.2.1.EvolutionaryAlgorithm -- 5.2.2.TheEateroftheRAutomaton:anExperimentalResult -- 5.3.NANDGate -- 5.3.1.Collisions -- 5.3.2.NewPattern -- 5.3.3.AssemblingPatternsintoaNOTGate -- 5.4.SimulationofOneCelloftheGameofLife -- 5.5.SimulationoftheGameofLife -- 5.5.1.IntersectionofStreams -- 5.5.2.Synchronisation. 327 $a5.5.3.SimulationoftheGameofLifeinR -- 6.Conclusion -- References -- Chapter10 ANUMERICALIMPLEMENTATIONOFANENCRYPTIONSYSTEMOFCOMPRESSEDSIGNALSWITHACELLULARAUTOMATAAPPROACH -- Abstract -- 1.Introduction -- 2.ElementaryCellularAutomata -- 3.EncryptionSystem -- 3.1.SynchronizationinCellularAutomata -- 3.1.1.Unidirectionalcoupling -- 3.1.2.Synchronization -- 3.2.TheBasicUnitCipher -- 4.PseudoRandomSequencesGenerator -- 4.1.ModifiedGenerator -- 4.2.PerformanceAnalysis -- 4.3.MultifractalPropertiesoftheMatrixHN -- 5.WaveletAnalysis -- 5.1.Introduction -- 5.2.WaveletTransform -- 5.3.CompressionScheme -- 6.NumericalImplementation -- 7.Conclusion -- References -- Chapter11 CANONICALFACTOROFCELLULARAUTOMATA -- Abstract -- Introduction -- 1.Definitions -- 2.Traces -- 2.1.FactorSubshifts -- 2.2.Generators -- 2.3.ColumnFactors -- 3.TracesofCellularAutomata -- 4.Equicontinuity -- 5.Expansivity -- 6.Entropy -- Conclusion -- References -- INDEX -- Blank Page. 330 $aA cellular automaton is a discrete model studied in computability theory, mathematics, physics, complexity science, theoretical biology and microstructure modeling. It consists of a regular grid of cells, each in one of a finite number of states, such as "On" or "Off". The grid can be in any finite number of dimensions. For each cell, a set of cells called its neighborhood (usually including the cell itself) is defined relative to the specified cell. This book presents current research from across the globe in the study of cellular automata, including using cellular automata to solve optimization problems; modeling drug release science using cellular automata; using the cellular automata model to study the dispersion of aphids and ladybugs in a block of citric trees; and the reversibility of cellular automata. 410 0$aMathematics research developments series. 410 0$aComputer science, technology and applications. 606 $aCellular automata 615 0$aCellular automata. 676 $a511.3/5 701 $aLi$b Thomas M$01871390 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910968475403321 996 $aCellular automata$94480201 997 $aUNINA