London: CRC Press, 2001. — 339 p.
This book introduces stochastic processes and their applications for students in engineering, industrial statistics, science, operations research, business, and finance. It provides the theoretical foundations for modeling time-dependent random phenomena encountered in these disciplines. Through numerous science and engineering-based examples and e
Probability Theory.
Stochastic Processes.
Poisson Processes.
Renewal Processes.
Discrete-Time Markov Chains.
Continuous-Time Markov Chains.
Wiener Processes.
Spectral Analysis of Stationary Processes.