230,66 €
256,29 €
-10% with code: EXTRA
Pattern Theory
Pattern Theory
230,66
256,29 €
  • We will send in 10–14 business days.
Pattern theory is a distinctive approach to the analysis of all forms of real-world signals. At its core is the design of a large variety of probabilistic models whose samples reproduce the look and feel of the real signals, their patterns, and their variability. Bayesian statistical inference then allows you to apply these models in the analysis of new signals. This book treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze s…
256.29
  • Publisher:
  • ISBN-10: 1568815794
  • ISBN-13: 9781568815794
  • Format: 15.2 x 22.9 x 2.4 cm, kieti viršeliai
  • Language: English
  • SAVE -10% with code: EXTRA

Pattern Theory (e-book) (used book) | David Mumford | bookbook.eu

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Pattern theory is a distinctive approach to the analysis of all forms of real-world signals. At its core is the design of a large variety of probabilistic models whose samples reproduce the look and feel of the real signals, their patterns, and their variability. Bayesian statistical inference then allows you to apply these models in the analysis of new signals.

This book treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze six representative classes of signals of increasing complexity. The book covers patterns in text, sound, and images. Discussions of images include recognizing characters, textures, nature scenes, and human faces. The text includes online access to the materials (data, code, etc.) needed for the exercises.

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  • Author: David Mumford
  • Publisher:
  • ISBN-10: 1568815794
  • ISBN-13: 9781568815794
  • Format: 15.2 x 22.9 x 2.4 cm, kieti viršeliai
  • Language: English English

Pattern theory is a distinctive approach to the analysis of all forms of real-world signals. At its core is the design of a large variety of probabilistic models whose samples reproduce the look and feel of the real signals, their patterns, and their variability. Bayesian statistical inference then allows you to apply these models in the analysis of new signals.

This book treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze six representative classes of signals of increasing complexity. The book covers patterns in text, sound, and images. Discussions of images include recognizing characters, textures, nature scenes, and human faces. The text includes online access to the materials (data, code, etc.) needed for the exercises.

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