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1. |
Record Nr. |
UNINA9910953995203321 |
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Autore |
Taruskin Richard |
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Titolo |
Music from the Earliest Notations to the Sixteenth Century |
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Pubbl/distr/stampa |
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Oxford University Press, USA, 2009 |
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ISBN |
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0-19-784613-0 |
0-19-979596-7 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (2008 p.) |
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Collana |
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The Oxford History of Western Music |
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Disciplina |
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Soggetti |
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Music -- 15th century -- History and criticism |
Music -- 16th century -- History and criticism |
Music -- 500-1400 -- History and criticism |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di contenuto |
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""Cover Page""; ""Title Page""; ""Copyright Page""; ""Dedication""; ""Contents""; ""Introduction""; ""Chapter 1 The Curtain Goes Up""; ""Chapter 2 New Styles and Forms""; ""Chapter 3 Retheorizing Music""; ""Chapter 4 Music of Feudalism and Fin' Amors""; ""Chapter 5 Polyphony in Practice And Theory""; ""Chapter 6 Notre Dame de Paris""; ""Chapter 7 Music for an Intellectual and Political Elite""; ""Chapter 8 Business Math, Politics, and Paradise: The Ars Nova""; ""Chapter 9 Machaut and His Progeny""; ""Chapter 10 "A Pleasant Place": Music of the Trecento""; ""Chapter 11 Island and Mainland"" |
""Chapter 12 Emblems and Dynasties""""Chapter 13 Middle and Low""; ""Chapter 14 Josquin and the Humanists""; ""Chapter 15 A Perfected Art""; ""Chapter 16 The End of Perfection""; ""Chapter 17 Commercial and Literary Music""; ""Chapter 18 Reformations and Counter-Reformations""; ""Chapter 19 Pressure of Radical Humanism""; ""Notes""; ""Art Credits""; ""Further Reading: A Checklist of Books in English""; ""Index"" |
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Sommario/riassunto |
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The universally acclaimed and award-winning Oxford History of Western Music is the eminent musicologist Richard Taruskin's provocative, erudite telling of the story of Western music from its earliest days to the present. Each book in this superlative five-volume set illuminates-through a representative sampling of masterworks- the |
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themes, styles, and currents that give shape and direction to a significant period in the history of Western music. Now in paperback, each of the volumes is being sold separate for the first time. This first volume in Richard Taruskin's majestic history, Music from t |
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2. |
Record Nr. |
UNINA9910427690903321 |
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Autore |
Helias Moritz |
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Titolo |
Statistical Field Theory for Neural Networks / / by Moritz Helias, David Dahmen |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XVII, 203 p. 127 illus., 5 illus. in color.) |
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Collana |
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Lecture Notes in Physics, , 1616-6361 ; ; 970 |
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Disciplina |
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Soggetti |
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Mathematical physics |
Neurosciences |
Machine learning |
Neural networks (Computer science) |
Computer science - Mathematics |
Mathematical statistics |
Theoretical, Mathematical and Computational Physics |
Neuroscience |
Machine Learning |
Mathematical Models of Cognitive Processes and Neural Networks |
Probability and Statistics in Computer Science |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction -- Probabilities, moments, cumulants -- Gaussian distribution and Wick’s theorem -- Perturbation expansion -- Linked cluster theorem -- Functional preliminaries -- Functional formulation of stochastic differential equations -- Ornstein-Uhlenbeck process: The free Gaussian theory -- Perturbation theory for stochastic differential equations -- Dynamic mean-field theory for random networks -- |
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Vertex generating function -- Application: TAP approximation -- Expansion of cumulants into tree diagrams of vertex functions -- Loopwise expansion of the effective action - Tree level -- Loopwise expansion in the MSRDJ formalism -- Nomenclature. |
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Sommario/riassunto |
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This book presents a self-contained introduction to techniques from field theory applied to stochastic and collective dynamics in neuronal networks. These powerful analytical techniques, which are well established in other fields of physics, are the basis of current developments and offer solutions to pressing open problems in theoretical neuroscience and also machine learning. They enable a systematic and quantitative understanding of the dynamics in recurrent and stochastic neuronal networks. This book is intended for physicists, mathematicians, and computer scientists and it is designed for self-study by researchers who want to enter the field or as the main text for a one semester course at advanced undergraduate or graduate level. The theoretical concepts presented in this book are systematically developed from the very beginning, which only requires basic knowledge of analysis and linear algebra. |
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