An update of this popular introduction to probability theory and information theory with new material on Markov chains.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
David Applebaum is a Professor in the Department of Probability and Statistics at the University of Sheffield.
Inhaltsangabe
Preface to the first edition Preface to the second edition 1. Introduction 2. Combinatorics 3. Sets and measures 4. Probability 5. Discrete random variables 6. Information and entropy 7. Communication 8. Random variables with probability density functions 9. Random vectors 10. Markov chains and their entropy Exploring further Appendix 1. Proof by mathematical induction Appendix 2. Lagrange multipliers Appendix 3. Integration of exp (-¿x²) Appendix 4. Table of probabilities associated with the standard normal distribution Appendix 5. A rapid review of Matrix algebra Selected solutions Index.
Preface to the first edition Preface to the second edition 1. Introduction 2. Combinatorics 3. Sets and measures 4. Probability 5. Discrete random variables 6. Information and entropy 7. Communication 8. Random variables with probability density functions 9. Random vectors 10. Markov chains and their entropy Exploring further Appendix 1. Proof by mathematical induction Appendix 2. Lagrange multipliers Appendix 3. Integration of exp (-¿x²) Appendix 4. Table of probabilities associated with the standard normal distribution Appendix 5. A rapid review of Matrix algebra Selected solutions Index.
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