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Stochastic Processes: Theory for Applications, by Robert G. Gallager
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This definitive textbook provides a solid introduction to discrete and continuous stochastic processes, tackling a complex field in a way that instils a deep understanding of the relevant mathematical principles, and develops an intuitive grasp of the way these principles can be applied to modelling real-world systems. It includes a careful review of elementary probability and detailed coverage of Poisson, Gaussian and Markov processes with richly varied queuing applications. The theory and applications of inference, hypothesis testing, estimation, random walks, large deviations, martingales and investments are developed. Written by one of the world's leading information theorists, evolving over twenty years of graduate classroom teaching and enriched by over 300 exercises, this is an exceptional resource for anyone looking to develop their understanding of stochastic processes.
- Sales Rank: #121870 in Books
- Published on: 2014-02-17
- Original language: English
- Number of items: 1
- Dimensions: 9.72" h x 1.22" w x 6.85" l, 2.50 pounds
- Binding: Hardcover
- 553 pages
About the Author
Robert G. Gallager is a Professor Emeritus at the Massachusetts Institute of Technology and one of the world's leading information theorists. He is a Fellow of the US National Academy of Engineering, the US National Academy of Sciences, and his numerous awards and honours include the IEEE Medal of Honour (1990) and the Marconi Prize (2003). He was awarded the MIT Graduate Student Teaching Award in 1993, and this book is based on his 20 years of experience of teaching this subject to students.
Most helpful customer reviews
12 of 14 people found the following review helpful.
Excellent Textbook
By The Twin
Stochastic Processes: Theory for Applications is very well written and does an excellent job of bridging the gap between intuition and mathematical rigorousness at the first-year graduate engineering school level. The book is a combination of the material from two MIT courses: (6.262) Discrete Stochastic Process and (6.432) Stochastic Processes, Detection, and Estimation. Because of this, the book shares much in common with Prof. Gallager's previous textbook: Discrete Stochastic Processes (ISBN-13: 978-0792395836 published 1995). I would not recommend to those interested only in this sub-topic - and who already own DSP - to purchase this new textbook as not much new will be gained. Nevertheless, the new inductee into the stochastic process world will be well served by this excellent update.
3 of 4 people found the following review helpful.
The BEST INTRO to Stochastic Processes
By Dr. Charles Saunders
The best intro to stochastic processes available, bar none [and I have seen a lot of them] - also a companion to his GREAT, FREE course on the MIT Open Course website. If you buy this book, plan to do the course - if you don't you are missing out on a massive amount of information.
0 of 6 people found the following review helpful.
Pairs well with a good glass of wine
By Michael Kellman
A calm and enjoyable read. Pairs well with a good glass of wine. I prefer red, but I’m sure white would work as well.
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