Dimensions of Uncertainty in Communication Engineering
- 1st Edition - July 6, 2022
- Imprint: Academic Press
- Author: Ezio Biglieri
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 9 2 7 5 - 6
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 9 2 7 6 - 3
Dimensions of Uncertainty in Communication Engineering is a comprehensive and self-contained introduction to the problems of nonaleatory uncertainty and the mathematical tools nee… Read more
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Request a sales quoteDimensions of Uncertainty in Communication Engineering is a comprehensive and self-contained introduction to the problems of nonaleatory uncertainty and the mathematical tools needed to solve them. The book gathers together tools derived from statistics, information theory, moment theory, interval analysis and probability boxes, dependence bounds, nonadditive measures, and Dempster–Shafer theory. While the book is mainly devoted to communication engineering, the techniques described are also of interest to other application areas, and commonalities to these are often alluded to through a number of references to books and research papers. This is an ideal supplementary book for courses in wireless communications, providing techniques for addressing epistemic uncertainty, as well as an important resource for researchers and industry engineers. Students and researchers in other fields such as statistics, financial mathematics, and transport theory will gain an overview and understanding on these methods relevant to their field.
- Uniquely brings together a variety of tools derived from statistics, information theory, moment theory, interval analysis and probability boxes, dependence bounds, nonadditive measures, and Dempster—Shafer theory
- Focuses on the essentials of various, wide-ranging methods with references to journal articles where more detail can be found if required
- Includes MIMO-related results throughout
Students, researchers and industry engineers in communication engineering; Students and researchers in financial mathematics and transport theory
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Preface
- Goal of this book
- Audience
- Tabula gratulatoria
- Bibliography
- Notations and symbols
- Acronyms and abbreviations
- 1: Model selection
- Abstract
- 1.1. Parametric models
- 1.2. Wireless channel models
- 1.3. Parameter estimation
- 1.4. Differential entropy and Kullback–Leibler divergence
- 1.5. KKT optimality conditions
- 1.6. Choosing the best model: the maximum-entropy principle
- 1.7. Choosing the best model in a set: Akaike Information Criterion
- 1.8. Choosing the best model in a set: minimum description length criterion
- Sources and parerga
- Bibliography
- 2: Performance bounds from epistemic uncertainty
- Abstract
- 2.1. Model robustness
- 2.2. Performance optimization with divergence constraints
- 2.3. Scenarios of uncertainty
- 2.4. Concentration-of-measure inequalities
- 2.5. Some applications
- 2.6. The certification problem
- Sources and parerga
- Bibliography
- 3: Moment bounds
- Abstract
- 3.1. Some classical results
- 3.2. The general moment-bound problem
- 3.3. Calculation of moments
- 3.4. Moments of unimodal pdfs
- 3.5. When is a sequence a valid moment sequence?
- 3.6. Moments in a parallelepiped
- 3.7. Geometric bounds
- 3.8. Quadrature-rule approximations and bounds
- 3.9. Čebyšev systems and principal representations
- 3.10. Moment problems as semidefinite programs
- 3.11. Multidimensional moment bounds and approximations
- Sources and parerga
- Bibliography
- 4: Interval analysis
- Abstract
- 4.1. Some definitions
- 4.2. Set operations on intervals
- 4.3. Algebraic operations on interval numbers
- 4.4. Interval vectors and matrices
- 4.5. Interval functions
- 4.6. The interval dependence problem
- 4.7. Integrals
- 4.8. Choosing a representative in an interval
- Sources and parerga
- Bibliography
- 5: Probability boxes
- Abstract
- 5.1. Interval probabilities
- 5.2. Generating probability boxes
- 5.3. Aggregating probability boxes
- 5.4. Combining probability boxes of random variables
- 5.5. Using probability boxes in performance evaluation
- Sources and parerga
- Bibliography
- 6: Dependence bounds
- Abstract
- 6.1. Copulas
- 6.2. Dependence p-boxes from copula bounds
- 6.3. Some examples of application
- 6.4. Bivariate dependence bounds on expectations
- 6.5. Bounds with monotone marginal densities
- 6.6. Deriving tighter dependence bounds
- Sources and parerga
- Bibliography
- 7: Beyond probability
- Abstract
- 7.1. Decisions under uncertainty
- 7.2. Epistemic vs. aleatory uncertainty
- 7.3. Lotteries, prospects, and utility functions
- 7.4. Other paradoxes arising from EUT
- 7.5. Upper and lower probabilities
- 7.6. Expected utility with interval probabilities
- 7.7. Some applications to digital communication
- 7.8. Going beyond probability
- 7.9. Set functions and their properties
- 7.10. Infinite sets
- 7.11. Capacities and Choquet integral
- 7.12. Expected values and Choquet integral
- 7.13. Dempster–Shafer theory
- Sources and parerga
- Bibliography
- Bibliography
- Bibliography
- Index
- Edition: 1
- Published: July 6, 2022
- Imprint: Academic Press
- No. of pages: 290
- Language: English
- Paperback ISBN: 9780323992756
- eBook ISBN: 9780323992763
EB
Ezio Biglieri
Ezio Biglieri received his formal training in Electrical Engineering at Politecnico di Torino (Italy), where he received his Dr. Engr. degree in 1967. Before being an Honorary Professor at University Pompeu Fabra, he was a Professor at Università di Napoli (Italy), at Politecnico di Torino (Italy), and at UCLA (USA). He has held visiting positions with Bell Labs (USA), the École Nationale Supérieure des Télécommunications (Paris, France), the University of Sydney (Australia), the Yokohama National University (Japan), Princeton University (USA), the University of South Australia, the Munich Institute of Technology (Germany), the National University of Singapore, the National Taiwan University, the University of Cambridge (U.K.), ETH Zurich (Switzerland), and Monash University Melbourne (Australia). Among other honors, in 2000 he received the IEEE Third-Millennium Medal and the IEEE Donald G. Fink Prize Paper Award, in 2001 the IEEE Communications Society Edwin Howard Armstrong Achievement Award, in 2004, 2012, and 2015 the Journal of Communications and Networks Best Paper Award, in 2012 the IEEE Information Theory Society Aaron D. Wyner Distinguished Service Award, and in 2021 the IEEE Communications Society Heinrich Hertz Award. He is a Life Fellow of the IEEE.
Affiliations and expertise
Universitat Pompeu Fabra, Barcelona, Spain.Read Dimensions of Uncertainty in Communication Engineering on ScienceDirect