Probability and Stochastic Pro

Yates, Roy D.

ISBN 10: 0471272140 / ISBN 13: 9780471272144

Verlag: Wiley, 2004

Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. Bestandsnummer des Verkäufers 00099286661

Inhaltsangabe:

This text introduces engineering students to probability theory and stochastic processes. Along with a thorough mathematical development of the subject, the book presents intuitive explanations of key points in order to give students the insights they need to apply the math to practical engineering problems. For each new principle it presents, the book provides an example of the application of the mathematics to an engineering problem. Each section ends with a quiz (with solutions posted on the book's web site) to help students gauge their understanding of the new material. Homework problems are annotated with symbols indicating their degree of difficulty. The initial five chapters contain the core material that will be present in any introductory course. In one-semester undergraduate courses, instructors will select material from the remaining seven chapters to meet their individual goals. Graduate students can cover all twelve chapters in one semester. All the techniques in the book are derived from a single, unifying model of an experiment consisting of a procedure and observations. The mathematical exposition begins with the axioms of probability and proceeds with clearly annotated definitions and theorems that convey the logical structure of the theory. To help students quickly understand the underlying principles of probability theory and to learn how to solve practical problems, the book introduces discrete random variables and continuous random variables in separate chapters. Clear, engaging, and always friendly
Maintaining their highly popular, user-friendly approach, Roy Yates and David Goodman demystify probability unlike any other text today. The authors help you develop an intuitive grasp of the principles of probability and stochastic processes, allowing you to successfully solve basic engineering problems using these principles... with a smile.
The authors present the principles of probability and stochastic processes as a logical sequence of building blocks that are clearly identified as an axiom, definition, or theorem. For each new principle, examples illustrate the application of the mathematics to engineering problems. You'll also have many opportunities for practice.
Now revised, this Second Edition features a new chapter on random vectors, expanded coverage of the applications of probability, a streamlined presentation of Markov chains and elementary queuing theory, and a tutorial in each chapter on using MATLAB.
With this text, you'll be able to:
Develop an intuitive understanding of the concepts.
Follow a single clear model that begins with an experiment consisting of a procedure and observations.
Put the theory into practice with an extensive collection of exercises (examples, quizzes, and homework problems).
Gain hands-on experience with MATLAB applications.
Master basic principles without the confusion of learning two different ways of calculating probabilities and averages at the same time. (Discrete and continuous random variables are treated separately.)

Über die Autorin bzw. den Autor: Dr. Roy Yates received the B.S.E. degree in 1983 from Princeton University, and the S.M. and Ph.D. degrees in 1986 and 1990 from M.I.T., all in Electrical Engineering. Since 1990, he has been with the Wireless Information Networks Laboratory (WINLAB) and the ECE department at Rutgers, University. He is currently an associate professor.

David J. Goodman is Director of WINLAB and a Professor of Electrical and Computer Engineering at Rutgers University. Before coming to Rutgers, he enjoyed a twenty year research career at Bell Labs where he was a Department Head in Communications Systems Research. He has made fundamental contributions to digital signal processing, speech coding, and wireless information networks.

Bibliografische Details

Titel: Probability and Stochastic Pro
Verlag: Wiley
Erscheinungsdatum: 2004
Einband: Hardcover
Zustand: Good