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LEADER 00000cam a2200805Ii 4500 
001    on1030840415 
003    OCoLC 
005    20200110051313.5 
006    m     o  d         
007    cr cnu|||||||| 
008    180103s2018    abca    ob    001 0 eng d 
016    (AMICUS)000045280213 
016    |z20179078674 (print) 
019    1030498445|a1030602066|a1030818554|a1030869633|a1055356222
       |a1115124418 
020    9781771992213|q(electronic bk.) 
020    1771992212|q(electronic bk.) 
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
       |z(OCoLC)1030818554|z(OCoLC)1030869633|z(OCoLC)1055356222
       |z(OCoLC)1115124418 
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-|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 
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|vCase studies. 
650  0 Music|xPhysiological aspects|vCase studies. 
650  0 Music|xPhilosophy and aesthetics|vCase studies. 
650  0 Neural networks (Computer science)|vCase studies. 
655  4 Electronic books. 
655  7 Case studies.|2fast|0(OCoLC)fst01423765 
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 
948    |d20200122|cEBSCO|tEBSCOebooksacademic NEW 12-21,1-17 
       11948|lridw 
994    92|bRID