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Methods In Algorithmic Analysis (Chapman & Hall/Crc Computer And Information Science Series)
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Explores The Impact Of The Analysis Of Algorithms On Many Areas Within And Beyond Computer Sciencea Flexible, Interactive Teaching Format Enhanced By A Large Selection Of Examples And Exercisesdeveloped From The Authors Own Graduatelevel Course, Methods In Algorithmic Analysis Presents Numerous Theories, Techniques, And Methods Used For Analyzing Algorithms. It Exposes Students To Mathematical Techniques And Methods That Are Practical And Relevant To Theoretical Aspects Of Computer Science.After Introducing Basic Mathematical And Combinatorial Methods, The Text Focuses On Various Aspects Of Probability, Including Finite Sets, Random Variables, Distributions, Bayes Theorem, And Chebyshev Inequality. It Explores The Role Of Recurrences In Computer Science, Numerical Analysis, Engineering, And Discrete Mathematics Applications. The Author Then Describes The Powerful Tool Of Generating Functions, Which Is Demonstrated In Enumeration Problems, Such As Probabilistic Algorithms, Compositions And Partitions Of Integers, And Shuffling. He Also Discusses The Symbolic Method, The Principle Of Inclusion And Exclusion, And Its Applications. The Book Goes On To Show How Strings Can Be Manipulated And Counted, How The Finite State Machine And Markov Chains Can Help Solve Probabilistic And Combinatorial Problems, How To Derive Asymptotic Results, And How Convergence And Singularities Play Leading Roles In Deducing Asymptotic Information From Generating Functions. The Final Chapter Presents The Definitions And Properties Of The Mathematical Infrastructure Needed To Accommodate Generating Functions.Accompanied By More Than 1,000 Examples And Exercises, This Comprehensive, Classroomtested Text Develops Students Understanding Of The Mathematical Methodology Behind The Analysis Of Algorithms. It Emphasizes The Important Relation Between Continuous (Classical) Mathematics And Discrete Mathematics, Which Is The Basis Of Computer Science.
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- Q: How many pages does this book have? A: This book has eight hundred twenty-six pages. It provides a comprehensive exploration of algorithm analysis with numerous examples and exercises.
- Q: What type of binding does this book have? A: This book is bound in hardcover. The durable binding helps ensure the book withstands frequent use in academic settings.
- Q: What are the dimensions of this book? A: The book measures seven point zero one inches in length, one point seventy-five inches in width, and ten inches in height. These dimensions make it a manageable size for reading.
- Q: What is the reading level for this book? A: This book is suitable for graduate-level students and above. It covers advanced topics in algorithm analysis, making it ideal for those with a foundational understanding of computer science.
- Q: How can I apply the concepts learned in this book? A: You can apply the concepts by working through the exercises and examples provided in the text. This practical approach helps reinforce theoretical knowledge in algorithm analysis.
- Q: Is this book suitable for beginners? A: No, this book is not suitable for beginners. It is designed for students who have prior knowledge of algorithms and mathematics.
- Q: How should I store this book to keep it in good condition? A: Store this book upright in a cool, dry place away from direct sunlight. This will help preserve the binding and prevent any warping of the pages.
- Q: Can I return this book if I am not satisfied? A: Yes, you can return the book if you are not satisfied. The seller offers a no-quibbles return policy to ensure customer satisfaction.
- Q: Is this book safe to use for academic purposes? A: Yes, this book is safe for academic use. It has been classroom-tested and is widely used in graduate-level courses.
- Q: How do I clean this book if it gets dirty? A: To clean the book, gently wipe the covers with a soft, dry cloth. Avoid using water or cleaning agents, as they can damage the pages.
- Q: What mathematical topics are covered in this book? A: The book covers various mathematical topics, including probability, recurrences, generating functions, and asymptotic analysis. These topics are essential for understanding algorithms.
- Q: Who is the author of this book? A: The author of this book is Vladimir A. Dobrushkin. He has developed this text from his own graduate-level course.
- Q: Does this book include exercises for practice? A: Yes, the book includes more than one thousand examples and exercises. These are designed to enhance understanding of algorithm analysis.
- Q: What is the primary focus of this book? A: The primary focus of this book is on the analysis of algorithms. It aims to bridge the gap between continuous and discrete mathematics in computer science.
- Q: Is there a specific audience for this book? A: Yes, the book is targeted towards graduate students and professionals in computer science. It is not intended for casual readers.