This applications oriented book features coverage of Markov chains and queuing theory which is of particular interest to communications professionals--a newer area where many professionals will need an update or refresher. It also features computer-based methods and exercises providing the most up-to-date training for those in the fields of telecommunications and computer engineering.

Probability and Random Processes for Electrical Engineering presents a carefully motivated, accessible, and interesting introduction to probability and random processes. It is designed to allow the instructor maximum flexibility in the selection of topics. In addition to the standard topics taught in introductory courses on probability, random variables, and random processes, the book includes sections on modeling, basic statistical techniques, computer simulation, reliability, and entropy, as well as concise but relatively complete introductions to Markov chains and queueing theory. The complexity of the systems encountered in electrical and computer engineering calls for an understanding of probability concepts and a facility in the use of probability tools from an increasing number of B.S. degree graduates. The introductory Course should therefore teach the student not only the basic theoretical concepts but also how to solve problems that arise in engineering practice. This course requires that the student develop problem-solving skills and understand how to make the transition from a real problem to a probability model for that problem. Relevance to Engineering Practice Motivating students is a major challenge in introductory probability courses. Instructors need to respond by showing students the relevance of probability theory to engineering practice. Chapter 1 addresses this challenge by discussing the role of probability models in engineering design. Practical applications from various areas of electrical and computer engineering are used to show how averages and relative frequencies provide the proper tools for handling the design of systems that involve randomness. These application areas are used in examples and problems throughout the text. From Problems to Probability Models The transition from real problems to probability models is shown in several ways. First, important concepts are usually developed by presenting real data or computer-simulated data. Second, sections on basic statistical techniques are integrated throughout the text. These sections demonstrate how statistical methods provide the link between theory and the real world. Finally, the significant random variables and random processes are developed using model-building arguments that range from simple to complex. For example, in Chapter 2 and 3, text discussion proceeds from coin tossing to Bernoulli trials. It then continues to the binomial and geometric distributions, and finally proceeds via limiting arguments to the Poisson, exponential, and Gaussian distributions. Examples and Problems Numerous examples in every section are used to demonstrate analytical and problem-solving techniques, develop concepts using simplified cases, and illustrate applications. The text includes over 700 problems, identified by section to help the instructor select homework problems. Additional sets of problems requiring cumulative knowledge are provided at the end of each chapter. Answers to selected problems are included at the end of the text. A Student Solutions Manual accompanies this text to develop problem-solving skills. A sampling of 25% of carefully worked out problems has been selected to help students understand concepts presented in the text. An Instructors Solutions Manual with complete solutions is also available. Computer Methods The development of an intuition for randomness can be aided by the use of computer exercises. Appendix C contains computer programs for generating several well-known random variables. The resulting data from computer-generated random numbers and variables can be analyzed using the statistical methods introduced in the text. Sections on computer methods have been integrated into the text rather than isolated in a separate ch