Introduction to stochastic processes

"This clear presentation of the most fundamental models of random phenomena employs methods that recognize computer-related aspects of theory. Topics include probability spaces and random variables, expectations and independence, Bernoulli processes and sums of independent random variables, Poisson processes, Markov chains and processes, and renewal theory. Includes an introduction to basic stochastic processes. 1975 edition"--

Reprint of: Englewood Cliffs, N.J. : Prentice-Hall, ©1975.

Cover; Title Page; Copyright Page; Contents; Preface; Chapter 1 Probability Spaces and Random Variables; 1. Probability Spaces; 2. Random Variables and Stochastic Processes; 3. Conditional Probability; 4. Exercises; Chapter 2 Expectations and Independence; 1. Expected Value; 2. Conditional Expectations; 3. Exercises; Chapter 3 Bernoulli Processes and Sums of Independent Random Variables; 1. Bernoulli Process; 2. Numbers of Successes; 3. Times of Successes; 4. Sums of Independent Random Variables; 5. Exercises; Chapter 4 Poisson Processes; 1. Arrival Counting Process; 2. Times of Arrivals.

3. Forward Recurrence Times4. Superposition of Poisson Processes; 5. Decomposition of Poisson Processes; 6. Compound Poisson Processes; 7. Non-stationary Poisson Processes; 8. Exercises; Chapter 5 Markov Chains; 1. Introduction; 2. Visits to a Fixed State; 3. Classification of States; 4. Exercises; Chapter 6 Limiting Behavior and Applications of Markov Chains; 1. Computation of R and F; 2. Recurrent States and the Limiting Probabilities; 3. Periodic States; 4. Transient States; 5. Applications to Queueing Theory: M/G/1 Queue; 6. Queueing System G/M/l; 7. Branching Processes; 8. Exercises.

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