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008 180103s2018 abca ob 001 0 eng d
016 (AMICUS)000045280213
016 |z20179078674 (print)
019 1030498445|a1030602066|a1030818554|a1030869633|a1055356222
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020 9781771992213|q(electronic book)
020 1771992212|q(electronic book)
020 9781771992206
020 1771992204
020 9781771992220
020 1771992220
020 |z1771992220
020 |z9781771992237
020 |z1771992239
024 3 9781771992206
035 (OCoLC)1030840415|z(OCoLC)1030498445|z(OCoLC)1030602066
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037 5330831|bProquest Ebook Central
040 UAB|beng|erda|epn|cUAB|dN$T|dEBLCP|dN$T|dOCLCF|dUWO|dYDX
|dNLC|dMERUC|dIDB|dUAB|dCELBN|dOCLCQ|dCEF|dINT|dVT2|dOTZ
|dOCLCQ|dDKU|dAGLDB|dCNTRU|dNLC|dUKAHL|dOCLCQ
049 RIDW
050 4 ML3830
055 0 ML3830|bD39 2018
055 07 ELEC MON E
072 7 MUS|x041000|2bisacsh
082 04 781.1/1|223
084 cci1icc|2lacc
084 coll13|2lacc
090 ML3830
100 1 Dawson, Michael Robert William,|d1959-|0https://id.loc.gov
/authorities/names/no99074527|eauthor.
245 10 Connectionist representations of tonal music :
|bdiscovering musical patterns by interpreting artificial
neural networks /|cMichael R.W. Dawson.
264 1 Edmonton, Alberta :|bAU Press,|c2018.
300 1 online resource (xv, 295 pages) :|billustrations
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
340 |gpolychrome|2rdacc
347 text file|2rdaft
504 Includes bibliographical references and index.
505 0 Cover; Half Title; Title; Copyright; Contents; List of
Figures; List of Tables; Acknowledgements; Overture: Alien
Music; Chapter 1: Science, Music, and Cognitivism; 1.1
Mechanical Philosophy, Mathematics, and Music; 1.2
Mechanical Philosophy and Tuning; 1.3 Psychophysics of
Music; 1.4 From Rationalism to Classical Cognitive
Science; 1.5 Musical Cognitivism; 1.6 Summary; Chapter 2:
Artificial Neural Networks and Music; 2.1 Some
Connectionist Basics; 2.2 Romanticism and Connectionism;
2.3 Against Connectionist Romanticism; 2.4 The Value Unit
Architecture; 2.5 Summary and Implications.
505 8 Chapter 3: The Scale Tonic Perceptron3.1 Pitch-Class
Representations of Scales; 3.2 Identifying the Tonics of
Musical Scales; 3.3 Interpreting the Scale Tonic
Perceptron; 3.4 Summary and Implications; Chapter 4: The
Scale Mode Network; 4.1 The Multilayer Perceptron; 4.2
Identifying Scale Mode; 4.3 Interpreting the Scale Mode
Network; 4.4 Tritone Imbalance and Key Mode; 4.5 Further
Network Analysis; 4.6 Summary and Implications; Chapter 5:
Networks for Key-Finding; 5.1 Key-Finding; 5.2 Key-Finding
with Multilayered Perceptrons; 5.3 Interpreting the
Network; 5.4 Coarse Codes for Key-Finding.
505 8 5.5 Key-Finding with Perceptrons5.6 Network
Interpretation; 5.7 Summary and Implications; Chapter 6:
Classifying Chords with Strange Circles; 6.1 Four Types of
Triads; 6.2 Triad Classification Networks; 6.3 Interval
Cycles and Strange Circles; 6.4 Added Note Tetrachords;
6.5 Classifying Tetrachords; 6.6 Interpreting the
Tetrachord Network; 6.7 Summary and Implications; Chapter
7: Classifying Extended Tetrachords; 7.1 Extended
Tetrachords; 7.2 Classifying Extended Tetrachords; 7.3
Interpreting the Extended Tetrachord Network; 7.4 Bands
and Coarse Coding; 7.5 Summary and Implications.
505 8 Chapter 8: Jazz Progression Networks8.1 The ii-V-I
Progression; 8.2 The Importance of Encodings; 8.3 Four
Encodings of the ii-V-I Problem; 8.4 Complexity, Encoding,
and Training Time; 8.5 Interpreting a Pitch-class
Perceptron; 8.6 The Coltrane Changes; 8.7 Learning the
Coltrane Changes; 8.8 Interpreting a Coltrane Perceptron;
8.9 Strange Circles and Coltrane Changes; 8.10 Summary and
Implications; Chapter 9: Connectionist Reflections; 9.1 A
Less Romantic Connectionism; 9.2 Synthetic Psychology of
Music; 9.3 Musical Implications; 9.4 Implications for
Musical Cognition; 9.5 Future Directions.
506 1 EPUB: Access restricted to LAC onsite clients.|fAccess
restricted to LAC onsite clients.|5CaOONL
506 0 PDF: Unrestricted online access.|fUnrestricted online
access.|5CaOONL
520 Intended to introduce readers to the use of artificial
neural networks in the study of music, this volume
contains numerous case studies and research findings that
address problems related to identifying scales, keys,
classifying musical chords, and learning jazz chord
progressions. A detailed analysis of networks is provided
for each case study which together demonstrate that
focusing on the internal structure of trained networks
could yield important contributions to the field of music
cognition.
590 eBooks on EBSCOhost|bEBSCO eBook Subscription Academic
Collection - North America
650 0 Music|xPsychological aspects|0https://id.loc.gov/
authorities/subjects/sh85088812|vCase studies.|0https://
id.loc.gov/authorities/subjects/sh99001484
650 0 Music|xPhysiological aspects|0https://id.loc.gov/
authorities/subjects/sh85088809|vCase studies.|0https://
id.loc.gov/authorities/subjects/sh99001484
650 0 Music|xPhilosophy and aesthetics|0https://id.loc.gov/
authorities/subjects/sh85088808|vCase studies.|0https://
id.loc.gov/authorities/subjects/sh99001484
650 0 Neural networks (Computer science)|0https://id.loc.gov/
authorities/subjects/sh90001937|vCase studies.|0https://
id.loc.gov/authorities/subjects/sh99001484
650 7 Music|xPsychological aspects.|2fast|0https://
id.worldcat.org/fast/1030418
650 7 Music|xPhysiological aspects.|2fast|0https://
id.worldcat.org/fast/1030411
650 7 Music|xPhilosophy and aesthetics.|2fast|0https://
id.worldcat.org/fast/1030408
650 7 Neural networks (Computer science)|2fast|0https://
id.worldcat.org/fast/1036260
655 4 Electronic books.
655 7 Case studies.|2fast|0https://id.worldcat.org/fast/1423765
655 7 Case studies.|2lcgft|0https://id.loc.gov/authorities/
genreForms/gf2017026140
776 08 |iPrint version:|aDawson, Michael R W.|tConnectionist
Representations of Tonal Music : Discovering Musical
Patterns by Interpreting Artifical Neural Networks.
|dEdmonton : Athabasca University Press, ©2018
|z9781771992206
856 40 |uhttps://rider.idm.oclc.org/login?url=http://
search.ebscohost.com/login.aspx?direct=true&scope=site&
db=nlebk&AN=1775041|zOnline eBook via EBSCO. Access
restricted to current Rider University students, faculty,
and staff.
856 42 |3Instructions for reading/downloading the EBSCO version
of this eBook|uhttp://guides.rider.edu/ebooks/ebsco
901 MARCIVE 20231220
948 |d20200122|cEBSCO|tEBSCOebooksacademic NEW 12-21,1-17
11948|lridw
994 92|bRID
