Ulteriori informazioni
Informationen zum 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. Klappentext 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. Inhaltsverzeichnis 1. Experiments! Models! and Probabilities2. Discrete Random Variables3. Continuous Random Variables4. Pairs of Random Variables5. Random Vectors6. Sums of Random Variables7. Parameter Estimation Using the Sample Mean8. Hypothesis Testing9. Estimation of a Random Variable10.Stochastic Processes11.Random Signal Processing12.Markov ChainsAppendicesReferencesIndex ...
Sommario
1. Experiments, Models, and Probabilities
2. Discrete Random Variables
3. Continuous Random Variables
4. Pairs of Random Variables
5. Random Vectors
6. Sums of Random Variables
7. Parameter Estimation Using the Sample Mean
8. Hypothesis Testing
9. Estimation of a Random Variable
10.Stochastic Processes
11.Random Signal Processing
12.Markov Chains
Appendices
References
Index
Relazione
"Excellent book. One of the best as a teaching tool. Yates' book is far better than Papoulis' book."
Aldo Morales, Penn State Harrisburg
