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140122 ||| eng |
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|a 9781475762808
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|a Mari, Jean-François
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| 245 |
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|a Probabilistic and Statistical Methods in Computer Science
|h Elektronische Ressource
|c by Jean-François Mari, René Schott
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| 250 |
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|a 1st ed. 2001
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| 260 |
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|a New York, NY
|b Springer US
|c 2001, 2001
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| 300 |
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|a XVI, 236 p. 11 illus
|b online resource
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| 505 |
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|a I Preliminaries -- 1. Probabilistic Tools -- 2. Statistical Tools -- II Applications -- 3. Some Applications in Algorithmics -- 4. Some Applications in Speech Recognition -- 5. Some Applications in Robotics -- Appendices -- A— Some useful statistical programs -- 1. The Gaussian density class -- 2. The Centroid class -- 3. The Top down clustering program -- References
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| 653 |
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|a Computer science
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| 653 |
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|a Statistics
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| 653 |
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|a Computer Science
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Probability Theory
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| 653 |
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|a Signal, Speech and Image Processing
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Signal processing
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| 653 |
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|a Statistics
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| 653 |
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|a Probabilities
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| 700 |
1 |
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|a Schott, René
|e [author]
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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| 028 |
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|a 10.1007/978-1-4757-6280-8
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| 856 |
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|u https://doi.org/10.1007/978-1-4757-6280-8?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 519.5
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| 520 |
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|a 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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