000 | 03775nam a22005175i 4500 | ||
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001 | 978-3-319-09888-3 | ||
003 | DE-He213 | ||
005 | 20200420220217.0 | ||
007 | cr nn 008mamaa | ||
008 | 140903s2014 gw | s |||| 0|eng d | ||
020 |
_a9783319098883 _9978-3-319-09888-3 |
||
024 | 7 |
_a10.1007/978-3-319-09888-3 _2doi |
|
050 | 4 | _aQA76.9.A43 | |
072 | 7 |
_aUMB _2bicssc |
|
072 | 7 |
_aCOM051300 _2bisacsh |
|
082 | 0 | 4 |
_a005.1 _223 |
100 | 1 |
_aVrajitoru, Dana. _eauthor. |
|
245 | 1 | 0 |
_aPractical Analysis of Algorithms _h[electronic resource] / _cby Dana Vrajitoru, William Knight. |
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2014. |
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300 |
_aXII, 466 p. 245 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aUndergraduate Topics in Computer Science, _x1863-7310 |
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505 | 0 | _aIntroduction -- Mathematical Preliminaries -- Fundamental Notations in Analysis of Algorithms -- Recurrence Relations -- Deterministic Analysis of Algorithms -- Algorithms and Probabilities -- Finite Graph Algorithms -- Appendix: Probability Theory. | |
520 | _aAnalysis of algorithms plays an essential role in the education and training of any serious programmer preparing to deal with real world applications. Practical Analysis of Algorithms introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts. Throughout the text, the explanations are aimed at the level of understanding of a typical upper-level student, and are accompanied by detailed examples and classroom-tested exercises. Topics and features: Includes numerous fully-worked examples and step-by-step proofs, assuming no strong mathematical background Describes the foundation of the analysis of algorithms theory in terms of the big-Oh, Omega, and Theta notations Examines recurrence relations, a very important tool used in the analysis of algorithms Discusses the concepts of basic operation, traditional loop counting, and best case and worst case complexities Reviews various algorithms of a probabilistic nature, and uses elements of probability theory to compute the average complexity of algorithms such as Quicksort Introduces a variety of classical finite graph algorithms, together with an analysis of their complexity Provides an appendix on probability theory, reviewing the major definitions and theorems used in the book This clearly-structured and easy-to-read textbook/reference applies a unique, practical approach suitable for professional short courses and tutorials, as well as for students of computer science. Dr. Dana Vrajitoru is an Associate Professor of Computer Science at Indiana University South Bend, IN, USA. Dr. William Knight is an Emeritus Associate Professor at the same institution. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aComputer programming. | |
650 | 0 | _aAlgorithms. | |
650 | 0 | _aComputer logic. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aAlgorithm Analysis and Problem Complexity. |
650 | 2 | 4 | _aLogics and Meanings of Programs. |
650 | 2 | 4 | _aProgramming Techniques. |
650 | 2 | 4 | _aAlgorithms. |
700 | 1 |
_aKnight, William. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783319098876 |
830 | 0 |
_aUndergraduate Topics in Computer Science, _x1863-7310 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-09888-3 |
912 | _aZDB-2-SCS | ||
942 | _cEBK | ||
999 |
_c51696 _d51696 |