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Partition Function (Mathematics): Probability Theory, Normalizing Constant, Information Science
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 (Buch) |
Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!
| Lieferstatus: |
i.d.R. innert 7-14 Tagen versandfertig |
| Veröffentlichung: |
März 2026
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| Genre: |
Schulbücher |
| ISBN: |
9786131091438 |
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EAN-Code:
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9786131091438 |
| Verlag: |
Omniscriptum |
| Einband: |
Kartoniert |
| Sprache: |
English
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| Dimensionen: |
H 220 mm / B 150 mm / D 6 mm |
| Gewicht: |
155 gr |
| Seiten: |
92 |
| Bewertung: |
Titel bewerten / Meinung schreiben
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| Inhalt: |
| Please note that the content of this book primarily consists of articles
available from Wikipedia or other free sources online. The partition
function or configuration integral, as used in probability theory,
information science and dynamical systems, is an abstraction of the
definition of a partition function in statistical mechanics. It is a
special case of a normalizing constant in probability theory, for the
Boltzmann distribution. The partition function occurs in many problems
of probability theory because, in situations where there is a natural
symmetry, its associated probability measure, the Gibbs measure, has the
Markov property. This means that the partition function occurs not only
in physical systems with translation symmetry, but also in such varied
settings as neural networks (the Hopfield network), and applications
such as genomics, corpus linguistics and artificial intelligence, which
employ Markov networks, and Markov logic networks. The Gibbs measure is
also the unique measure that has the property of maximizing the entropy
for a fixed expectation value of the energy; this underlies the
appearance of the partition function in maximum entropy methods and the
algorithms derived therefrom. |
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