A self-contained treatment of stochastic processes arising from models for queues, insurance risk, and dams and data communication, using their sample function

This book is based on a course I have taught at Cornell University since 1965. The primary topic of this course was queueing theory, but related topics such as

Stochastic processes are necessary ingredients for building models of a wide variety of phenomena exhibiting time varying randomness. This text offers easy acce

Stochastic Image Processing provides the first thorough treatment of Markov and hidden Markov random fields and their application to image processing. Although

Let X(t) be the level of the storage process at time t; X(0) = 0. Starting at time 0, the level X(t) increases linearly with slope s sub i for a random length o