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Judul Lectures on probability, information and large scale behaviour / Matteo Marsili
Pengarang Marsili, Matteo
Penerbitan Italy : SISSA, 2025
Deskripsi Fisik 396 p :ill
ISBN 9788898587063
Subjek PROBALITY
STATISTICAL PHYSICS
Abstrak This book stems from lecture notes prepared by the author over decades of teaching. It is divided into two parts. The first part focuses on classical probability, with the aim of helping students develop a solid intuition about random phenomena. It guides them in translating real-world problems into probabilistic language and equips them with the tools needed to derive quantitative insights. The second part investigates the typical behaviours that emerge in asymptotic regimes -- such as the law of large numbers, limit theorems, and large deviations -- and elucidates their connection to information theory. This latter part offers a unifying perspective, based on principles of information theory and statistical mechanics, for understanding large-scale phenomena like phase transitions that appear across disciplines such as statistical physics, inference, coding theory, and computer science.
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Lokasi Akses Online https://directory.doabooks.org/handle/20.500.12854/162599

 
No Barcode No. Panggil Akses Lokasi Ketersediaan
098526192 519.2 Mat l Baca Online Perpustakaan Pusat - Online Resources
Ebook
Tersedia
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245 1 # $a Lectures on probability, information and large scale behaviour /$c Matteo Marsili
260 # # $a Italy :$b SISSA,$c 2025
300 # # $a 396 p : $b ill
520 # # $a This book stems from lecture notes prepared by the author over decades of teaching. It is divided into two parts. The first part focuses on classical probability, with the aim of helping students develop a solid intuition about random phenomena. It guides them in translating real-world problems into probabilistic language and equips them with the tools needed to derive quantitative insights. The second part investigates the typical behaviours that emerge in asymptotic regimes -- such as the law of large numbers, limit theorems, and large deviations -- and elucidates their connection to information theory. This latter part offers a unifying perspective, based on principles of information theory and statistical mechanics, for understanding large-scale phenomena like phase transitions that appear across disciplines such as statistical physics, inference, coding theory, and computer science.
650 # # $a PROBALITY
650 # # $a STATISTICAL PHYSICS
856 # # $a https://directory.doabooks.org/handle/20.500.12854/162599
990 # # $a 098526192
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