| Algorithmic Algebra 1993 Edition Contributor(s): Mishra, Bhubaneswar (Author) |
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ISBN: 0387940901 ISBN-13: 9780387940908 Publisher: Springer OUR PRICE: $52.24 Product Type: Hardcover - Other Formats Published: September 1993 Annotation: A self-contained text that acquaints advanced undergraduate and graduate students in computer science, engineering and mathematics with the algorithmic ideas in computer algebra. An ideal text for classroom use or self-study. |
| Additional Information |
| BISAC Categories: - Mathematics | Algebra - General - Science |
| Dewey: 512.002 |
| LCCN: 92014094 |
| Series: Monographs in Computer Science |
| Physical Information: 1.01" H x 6.37" W x 9.47" (1.72 lbs) 420 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: Algorithmic Algebra studies some of the main algorithmic tools of computer algebra, covering such topics as Gr bner bases, characteristic sets, resultants and semialgebraic sets. The main purpose of the book is to acquaint advanced undergraduate and graduate students in computer science, engineering and mathematics with the algorithmic ideas in computer algebra so that they could do research in computational algebra or understand the algorithms underlying many popular symbolic computational systems: Mathematica, Maple or Axiom, for instance. Also, researchers in robotics, solid modeling, computational geometry and automated theorem proving community may find it useful as symbolic algebraic techniques have begun to play an important role in these areas. The book, while being self-contained, is written at an advanced level and deals with the subject at an appropriate depth. The book is accessible to computer science students with no previous algebraic training. Some mathematical readers, on the other hand, may find it interesting to see how algorithmic constructions have been used to provide fresh proofs for some classical theorems. The book also contains a large number of exercises with solutions to selected exercises, thus making it ideal as a textbook or for self-study. |