Probability, Random Variables and Stochastic Processes

ISBN-10: 0073660116
ISBN-13: 9780073660110
Edition: 4th 2002
List price: $295.67 Buy it from $174.00
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Description: The fourth edition of Probability, Random Variables and Stochastic Processes has been updated significantly from the previous edition, and it now includes co-author S. Unnikrishna Pillai of Polytechnic University. The book is intended for a  More...

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Book details

List price: $295.67
Edition: 4th
Copyright year: 2002
Publisher: McGraw-Hill Higher Education
Publication date: 10/25/2001
Binding: Hardcover
Pages: 864
Size: 7.25" wide x 9.25" long x 1.25" tall
Weight: 3.190
Language: English

The fourth edition of Probability, Random Variables and Stochastic Processes has been updated significantly from the previous edition, and it now includes co-author S. Unnikrishna Pillai of Polytechnic University. The book is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, math, and physics departments. The authors' approach is to develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineering interest. Approximately 1/3 of the text is new material--this material maintains the style and spirit of previous editions. In order to bridge the gap between concepts and applications, a number of additional examples have been added for further clarity, as well as several new topics.

Preface
Probability and Random Variables
The Meaning of Probability
Introduction
The Definitions
Probability and Induction
Causality Versus Randomness
The Axioms of Probability
Set Theory
Probability Space
Conditional Probability
Problems
Repeated Trials
Combined Experiments
Bernoulli Trials
Bernoulli's Theorem and Games of Chance
Problems
The Concept of a Random Variable
Introduction
Distribution and Density Functions
Specific Random Variables
Conditional Distributions
Asymptotic Approximations for Binomial Random Variable
Problems
Functions of One Random Variable
The Random Variable g(x)
The Distribution of g(x)
Mean and Variance
Moments
Characteristic Functions
Problems
Two Random Variables
Bivariate Distributions
One Function of Two Random Variables
Two Functions of Two Random Variables
Joint Moments
Joint Characteristic Functions
Conditional Distributions
Conditional Expected Values
Problems
Sequences of Random Variables
General Concepts
Conditional Densities, Characteristic Functions, and Normality
Mean Square Estimation
Stochastic Convergence and Limit Theorems
Random Numbers: Meaning and Generation
Problems
Statistics
Introduction
Estimation
Parameter Estimation
Hypothesis Testing
Problems
Stochastic Processes
General Concepts
Definitions
Systems with Stochastic Inputs
The Power Spectrum
Discrete-Time Processes
Continuity, Differentiation, Integration
Shift Operators and Stationary Processes
Problems
Random Walks and Other Applications
Random Walks
Poisson Points and Shot Noise
Modulation
Cyclostationary Processes
Bandlimited Processes and Sampling Theory
Deterministic Signals in Noise
Bispectra and System Identification
The Poisson Sum Formula
The Schwarz Inequality
Problems
Spectral Representation
Factorization and Innovations
Finite-Order Systems and State Variables
Fourier Series and Karhunen-Loeve Expansions
Spectral Representation of Random Processes
Problems
Spectrum Estimation
Ergodicity
Spectrum Estimation
Extrapolation and System Identification
The General Class of Extrapolating Spectra and Youla's Parametrization
Minimum-Phase Functions
All-Pass Functions
Problems
Mean Square Estimation
Introduction
Prediction
Filtering and Prediction
Kalman Filters
Problems
Entropy
Introduction
Basic Concepts
Random Variables and Stochastic Processes
The Maximum Entropy Method
Coding
Channel Capacity
Problems
Markov Chains
Introduction
Higher Transition Probabilities and the Chapman-Kolmogorov Equation
Classification of States
Stationary Distributions and Limiting Probabilities
Transient States and Absorption Probabilities
Branching Processes
Mixed Type Population of Constant Size
Structure of Periodic Chains
Problems
Markov Processes and Queueing Theory
Introduction
Markov Processes
Queueing Theory
Networks of Queues
Problems
Bibliography
Index

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