The thoroughly revised second edition of this innovative introduction by a leading scholar and editor of Austen's work explains what students need to know about her novels, life, context and reception. An essential purchase for students of Austen, as well as readers wanting to deepen their appreciation of the novels.
The thoroughly revised second edition of this innovative introduction by a leading scholar and editor of Austen's work explains what students need to know about her novels, life, context and reception. An essential purchase for students of Austen, as well as readers wanting to deepen their appreciation of the novels.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Bruce Hajek has been an avid student, instructor, and user of probability theory for his entire career. He is the Mary Lou and Leonard C. Hoeft Chair of Engineering, Center for Advanced Study Professor of Electrical and Computer Engineering, and Professor in the Coordinated Science Laboratory at the University of Illinois. Among his many awards, he is a member of the US National Academy of Engineering and a recipient of the IEEE Koji Kobayashi Computers and Communications Award. He is co-author, with E. Wong, of the more advanced classic book, Stochastic Processes in Engineering Systems, 2nd edition (1985).
Inhaltsangabe
1. A selective review of basic probability 2. Convergence of a sequence of random variables 3. Random vectors and minimum mean squared error estimation 4. Random processes 5. Inference for Markov models 6. Dynamics for countable-state Markov models 7. Basic calculus of random processes 8. Random processes in linear systems and spectral analysis 9. Wiener filtering 10. Martingales 11. Appendix 12. Solutions to even numbered problems.
1. A selective review of basic probability 2. Convergence of a sequence of random variables 3. Random vectors and minimum mean squared error estimation 4. Random processes 5. Inference for Markov models 6. Dynamics for countable-state Markov models 7. Basic calculus of random processes 8. Random processes in linear systems and spectral analysis 9. Wiener filtering 10. Martingales 11. Appendix 12. Solutions to even numbered problems.
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