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Probabilistic and Statistical Methods in Computer Science

Bag om Probabilistic and Statistical Methods in Computer Science

Probabilistic and Statistical Methods in Computer Science presents a large variety of applications of probability theory and statistics in computer science and more precisely in algorithm analysis, speech recognition and robotics. It is written on a self-contained basis: all probabilistic and statistical tools needed are introduced on a comprehensible level. In addition all examples are worked out completely. Most of the material is scattered throughout available literature. However, this is the first volume that brings together all of this material in such an accessible format. Probabilistic and Statistical Methods in Computer Science is intended for students in computer science and applied mathematics, for engineers and for all researchers interested in applications of probability theory and statistics. It is suitable for self study as well as being appropriate for a course or seminar.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9781441948779
  • Indbinding:
  • Paperback
  • Sideantal:
  • 256
  • Udgivet:
  • 3. december 2010
  • Størrelse:
  • 155x15x235 mm.
  • Vægt:
  • 394 g.
  • BLACK NOVEMBER
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Leveringstid: 8-11 hverdage
Forventet levering: 27. november 2024

Beskrivelse af Probabilistic and Statistical Methods in Computer Science

Probabilistic and Statistical Methods in Computer Science presents a large variety of applications of probability theory and statistics in computer science and more precisely in algorithm analysis, speech recognition and robotics. It is written on a self-contained basis: all probabilistic and statistical tools needed are introduced on a comprehensible level. In addition all examples are worked out completely.
Most of the material is scattered throughout available literature. However, this is the first volume that brings together all of this material in such an accessible format.
Probabilistic and Statistical Methods in Computer Science is intended for students in computer science and applied mathematics, for engineers and for all researchers interested in applications of probability theory and statistics. It is suitable for self study as well as being appropriate for a course or seminar.

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