Probability models for computer science
著者
書誌事項
Probability models for computer science
Harcourt/Academic Press, c2002
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注記
Includes bibliographical references (p. 283) and index
内容説明・目次
内容説明
The role of probability in computer science has been growing for years and, in lieu of a tailored textbook, many courses have employed a variety of similar, but not entirely applicable, alternatives. To meet the needs of the computer science graduate student (and the advanced undergraduate), best-selling author Sheldon Ross has developed the premier probability text for aspiring computer scientists involved in computer simulation and modeling. The math is precise and easily understood. As with his other texts, Sheldon Ross presents very clear explanations of concepts and covers those probability models that are most in demand by, and applicable to, computer science and related majors and practitioners.
目次
- Review of Probability
- Some Examples
- Poisson and Compound Poisson Variables
- Approximations and Processes
- Markov Chains
- Queuing
- Random Algorithms and the Probabilistic Method
- Martingales
- Simulation.
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