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PROBABILITY, RANDOM VARIABLES, AND …

probability , RANDOMVARIABLES, ANDSTOCHASTIC PROCESSESFOURTH EDITIONA thanasios PapoulisUniversity ProfessorPolytechnic UniversityS. Unnikrishna PillaiProfessor of Electrical and Computer EngineeringPolytechnic UniversityMeGrawHillBoston Burr Ridge, IL Dubuque, IA Madison, Wl New York San Francisco St. LouisBangkok Bogota Caracas Kuala Lumpur Lisbon London Madrid Mexico CityMilan Montreal New Delhi Santiago Seoul Singapore Sydney Taipei TorontoCONTENTSP reface ixPART I probability AND RANDOM VARIABLES 1 Chapter 1 The Meaning of probability 31-1 Introduction / 1-2 The Definitions / 1-3 Probabilityand Induction / 1-4 Causality Versus RandomnessChapter 2

PROBABILITY, RANDOM VARIABLES, AND STOCHASTIC PROCESSES FOURTH EDITION Athanasios Papoulis University Professor Polytechnic University S. …

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Transcription of PROBABILITY, RANDOM VARIABLES, AND …

1 probability , RANDOMVARIABLES, ANDSTOCHASTIC PROCESSESFOURTH EDITIONA thanasios PapoulisUniversity ProfessorPolytechnic UniversityS. Unnikrishna PillaiProfessor of Electrical and Computer EngineeringPolytechnic UniversityMeGrawHillBoston Burr Ridge, IL Dubuque, IA Madison, Wl New York San Francisco St. LouisBangkok Bogota Caracas Kuala Lumpur Lisbon London Madrid Mexico CityMilan Montreal New Delhi Santiago Seoul Singapore Sydney Taipei TorontoCONTENTSP reface ixPART I probability AND RANDOM VARIABLES 1 Chapter 1 The Meaning of probability 31-1 Introduction / 1-2 The Definitions / 1-3 Probabilityand Induction / 1-4 Causality Versus RandomnessChapter 2 The Axioms of probability

2 152-1 Set Theory / 2-2 probability Space / 2-3 ConditionalProbability / ProblemsChapter 3 Repeated Trials 463-1 Combined Experiments / 3-2 BernoulliTrials / 3-3 Bernoulli's Theorem and Games ofChance / ProblemsChapter 4 The Concept of a RANDOM variable 724-1 Introduction / 4-2 Distribution and DensityFunctions / 4-3 Specific RANDOM Variables / 4-4 ConditionalDistributions / 4-5 Asymptotic Approximations for BinomialRandom variable / ProblemsChapter 5 Functions of One RANDOM variable 1235-1 The RANDOM variable g(x) I 5-2 The Distributionofg(x)

3 / 5-3 Mean and Variance / 5-4 Moments /5-5 Characteristic Functions / ProblemsChapter 6 Two RANDOM Variables 1696-1 Bivariate Distributions / 6-2 One Function of Two RandomVariables / 6-3 Two Functions of Two RandomVariables / 6-4 Joint Moments / 6-5 Joint CharacteristicFunctions / 6-6 Conditional Distributions / 6-7 ConditionalExpected Values / ProblemsVI CONTENTSC hapter 7 Sequences of RANDOM Variables 2437-1 General Concepts / 7-2 Conditional Densities,Characteristic Functions, and Normality / 7-3 Mean SquareEstimation / 7-4 stochastic Convergence and LimitTheorems / 7-5 RANDOM Numbers.

4 Meaning andGeneration / ProblemsChapter 8 Statistics 3038-1 Introduction / 8-2 Estimation / 8-3 ParameterEstimation / 8-4 Hypothesis Testing / ProblemsPART II stochastic processes 371 Chapter 9 General Concepts 3739-1 Definitions / 9-2 Systems with stochastic Inputs /9-3 The Power Spectrum / 9-4 Discrete-Time processes /Appendix 9A Continuity, Differentiation, Integration /Appendix 9B Shift Operators and StationaryProcesses / ProblemsChapter 10 RANDOM Walks and Other Applications 43510-1 RANDOM Walks / 10-2 Poisson Points and ShotNoise / 10-3 Modulation / 10-4 CyclostationaryProcesses / 10-5 Bandlimited processes and SamplingTheory / 10-6 Deterministic Signals in Noise / 10-7 Bispectraand System Identification / Appendix 10A The Poisson SumFormula / Appendix 10B The Schwarz Inequality / ProblemsChapter 11 Spectral Representation

5 49911-1 Factorization and Innovations / 11-2 Finite-Order Systemsand State Variables / 11-3 Fourier Series and Karhunen-LoeveExpansions / 11-4 Spectral Representation of RandomProcesses / ProblemsChapter 12 Spectrum Estimation L 52312-1 Ergodicity / 12-2 SpectrumEstimation / 12-3 Extrapolation and SystemIdentification / 12-4 The General Class of Extrapolating Spectraand Youla's Parametrization / Appendix 12A Minimum-PhaseFunctions / Appendix 12B All-Pass Functions / ProblemsChapter 13 Mean Square Estimation 58013-1 Introduction / 13-2 Prediction / 13-3 Filtering andPrediction / 13-4 Kalman Filters / ProblemsChapter 14 Entropy ' 62914-1 Introduction / 14-2 Basic Concepts / 14-3 RandomVariables and stochastic processes / 14-4 The MaximumEntropy Method / 14-5 Coding / 14-6 ChannelCapacity / ProblemsCONTENTS VllChapter 15 Markov Chains

6 69515-1 Introduction / 15-2 Higher Transition Probabilities and theChapman-Kolmogorov Equation / 15-3 Classification ofStates / 15-4 Stationary Distributions and LimitingProbabilities / 15-5 Transient States and AbsorptionProbabilities / 15-6 Branching processes / Appendix 15 AMixed Type Population of Constant Size / Appendix 15 BStructure of Periodic Chains / ProblemsChapter 16 Markov processes and Queueing Theory 77316-1 Introduction / 16-2 Markov processes / 16-3 QueueingTheory / 16-4 Networks of Queues / ProblemsBibliography 835 Index 837


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