Discrete Algorithmic Mathematics

Discrete Algorithmic Mathematics

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Thoroughly revised for a one-semester course, this well-known and highly regarded book is an outstanding text for undergraduate discrete mathematics. It has been updated with new or extended discussions of order notation, generating functions, chaos, aspects of statistics, and computational biology. Written in a lively, clear style that talks to the reader, the book is unique for its emphasis on algorithmics and the inductive and recursive paradigms as central mathematical themes. It includes a broad variety of applications, not just to mathematics and computer science, but to natural and social science as well.
A manual of selected solutions is available for sale to students; see sidebar. A complete solution manual is available free to instructors who have adopted the book as a required text.
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Product details

  • Hardback | 803 pages
  • 191 x 241 x 51.05mm | 1,701g
  • A K Peters
  • Natick, United States
  • English
  • New edition
  • 3rd New edition
  • 9/1/11 - book went back to Replika per JL
  • 1568811667
  • 9781568811666
  • 536,560

Review quote

The exposition is self-contained, complemented by diverse exercises and also accompanied by an introduction to mathematical reasoning ... this book is an excellent textbook for a one-semester undergraduate course and it includes a lot of additional material to choose from.
-EMS, March 2006

In a textbook, it is necessary to select carefully the statements and difficulty of the problems ... in this textbook, this is fully achieved ... This review considers this book an excellent one.
-The Mathematical Gazette, March 2006
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About Stephen B. Maurer

Stephen B Maurer (Ph.D. Princeton 1972) is a Professor of Mathematics at Swarthmore College and winner of the Allendoerfer Award for expository writing. Anthony Ralston (Ph.D. MIT 1956) is Professor Emeritus of Computer Science and Mathematics at SUNY Buffalo. He is a former President of the ACM.
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Rating details

8 ratings
3 out of 5 stars
5 25% (2)
4 0% (0)
3 25% (2)
2 50% (4)
1 0% (0)
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