This article is devoted to the study of instrumental sonatas by composers of Baroque, Classicism, and Romanticism periods. Within the study, the overall number of notes, number of repeated, lowered and raised notes, maximum interval, and range of musical passage are examined. Six subhypotheses are tested to learn the differences in musical works. The analysis is carried out by Student's t-test and Kruskal–Wallis test. The analysis results manifest that four of the six analysed parameters depend on the era of composing. Therefore, these parameters can be used to identify the period of writing a musical piece.
BargagliottiAnna E., and GreenwellRaymond. 2015. “Combinatorics and Statistical Issues Related to the Kruskal–Wallis Statistic. ” Communications in Statistics – Simulation and Computation 44: 533–550. doi: 10.1080/03610918.2013.786781.
2.
BassiouNikolleta, KotropoulosConstantine, and Papazoglou-ChalikiasAnastasios. 2015. “
Greek Folk Music Classification into Two Genres Using Lyrics and Audio via Canonical Correlation Analysis. ” In 9th International Symposium on Image and Signal Processing and Analysis , edited by NikolletaBassiou, ConstantineKotropoulos, and AnastasiosPapazoglou-Chalikias, 238–243. Zagreb: IEEE. doi: 10.1109/ISPA.2015.7306065
3.
CrawfordTim, and GibsonLorna. 2016. “
On the Use of Computational Methods for Expressive Music Performance. ” In Modern Methods for Musicology , edited by TimCrawford, and LornaGibson, 113–134. London: Routledge.
4.
DeloguFranco, LorenzoPietro, MaioPeppe, and BelardinelliOlivetti. 2015. “Comparison Between a Behavior and a Mathematical Classification of Music Distances: A Pilot Research . ” 5th Conference Understanding and Creating music. 69–75.
5.
EdelsonJill, and JohnsonGretchen. 2012. “Music Makes Math Meaningful. ” Childhood Education 80 (2): 65–70. doi: 10.1080/00094056.2004.10521259.
6.
ElaineChew, GerardAssayag, and SmithJordan. 2016. Mathemusical Conversations: Mathematics and Computation in Music Performance and Composition (Vol. 32) . Singapore: World Scientific.
7.
GierrJames.1996. The Critical Editing of Music: History, Method, and Practice . Cambridge: Cambridge University Press.
8.
GoncalvesClara, and SoaresMaria. 2016. “
Le Corbusier: Architecture, Music, Mathematics: Longing for Classicism?
” In En Le Corbusier. 50 añosdespués , edited by ClaraGoncalves, and MariaSoares, 844–861. Valencia: Editorial UniversitatPolitècnica de València. doi: 10.4995/LC2015.2015.791
9.
GrennlandSander, SennStephen, RothmanKenneth, CarlingJohn, PooleCharles, GoodmanSteven, and AltmanDouglas. 2016. “Statistical Tests, P Values, Confidence Intervals, and Power: A Guide to Misinterpretations. ” European Journal of Epidemiology 31 (4): 337–350. doi: 10.1007/s10654-016-0149-3.
10.
HansenNiels, SadakataMakiko, and PearceMarcus. 2016. “Nonlinear Changes in the Rhythm of European Art Music Quantitative Support for Historical Musicology. ” Music Perception: An Interdisciplinary Journal 33 (4): 414–431. doi: 10.1525/mp.2016.33.4.414.
11.
HerremansDorien, SorensenKenneth, and MartensDavid. 2015. “Classification and Generation of Composer-Specific Music Using Global Feature Models and Variable Neighborhood Search. ” Computer Music Journal 39 (3): 71–91. doi: 10.1162/COMJ_a_00316.
12.
KempfertKatherine, and WongSamuel. 2018. Where Does Haydn End and Mozart Begin? Composer Classification of String Quartets . New York: Cornell University.
13.
LahhamFatima.2017. “Continental Baroque: Music for Diverse Flute. ” Early Music 45 (1): 159–161. doi: 10.1093/em/cax046.
14.
LeachElizabeth.2018. Sung Birds: Music, Nature, and Poetry in the Later Middle Age . New York: Cornell University Press.
15.
LiouCheng-yuan, SimakAlexandr, and ChengWei-chen. 2015. “Complexity Analysis of Music. ” Complexity 21 (S1): 263–268.
16.
LockeRalph.2015. Music and the Exotic from the Renaissance to Mozart . Cambridge: Cambridge University Press.
17.
LosseffNicky.2004. The Idea of Music in Victorian Fiction . 1st ed. London: Routledge.
18.
MartorellAgustin, and GomezEmilia. 2014. “Hierarchical Multi-Scale Set-class Analysis. ” Journal of Mathematics and Music 9 (1): 95–108. doi: 10.1080/17459737.2014.906072.
19.
McGeeTimothy.2017. Instruments and Their Music in the Middle Ages . London: Routledge.
20.
MeredithDavid.2016. Computational Music Analysis . Heidelberg: Springer.
21.
ParkChanseok.2018. Note on the Robustification of the Student t-Test Statistic Using the Median and the Median Absolute Deviation . New York: Cornell University.
22.
ParkDoheum, BaeArram, SchichMaximilian, and ParkJuyong. 2015. “Topology and Evolution of the Network of Western Classical Music Composers. ” EPJ Data Science 4 (1): 2–13. doi: 10.1140/epjds/s13688-015-0039-z.
23.
RakaiZsuzsa.2017. “‘
New Classicism’ and the Music of ‘new Humanity’ – Hungarian Music Historiography and BenceSzabolcsi. ” AK Journal 31 (2): 191–198. doi: 10.1556/044.2017.32.1.6.
24.
RenIris, KoopsHendrick, BountouridisDimitrious, VolkAnja, SwierstraWouter, and VeltcampRemco. 2018. “
Feature Analysis of Repeated Patterns in Dutch Folk Songs Using Principal Component Analysis. ” In Proceedings of the 8th International Workshop on Folk Music Analysis (FMA2018) , edited by IrisRen, HendrickKoops, DimitriousBountouridis, AnjaVolk, WouterSwierstra, and RemcoVeltcamp, 86–88. Thessaloniki: Aristotle University of Thessaloniki.
25.
RobertsGareth.2016. From Music to Mathematics: Exploring the Connections . 1st ed.Baltimore: Johns Hopkins University Press.
26.
RydénJesper.2020. “On Features of Fugue Subjects. A Comparison of JS Bach and Later Composers. ” Journal of Mathematics and Music 14 (1): 1–20. doi: 10.1080/17459737.2019.1610193.
27.
ShaferJennifer.2010. The Two-part and Three-part Inventions of Bach: A Mathematical Analysis . Marshal: East Texas Baptist University.
28.
TalbotMichael.2015. “Paduan Baroque and Franciscan Musicians: The Contribution of the Conventual Masters. Proceedings of the XVI International Conference on the Po Valley Baroque (17th-18th Centuries). ” Music & Letters 96 (3): 454–457.
29.
TirnakleUgur, and BorgesErnesto. 2016. “The Standard map: From Boltzmann-Gibbs Statistics to Tsallis Statistics. ” Scientific Report 6: 23644. doi: 10.1038/srep23644.
30.
VelardeGissel, WeydeTillman, ChaconCarlos Cancino, MeredithDavid, and GrachtenMaarten. 2016. “
Composer Recognition Based on 2D-Filtered Piano-Rolls. ” In Proceedings of the 17th International Conference on Music Information Retrieval , 17 ed., edited by GisselVelarde, Carlos CancinoChacon, TillmanWeyde, DavidMeredith, and MaartenGrachten, 115–121. Canada: International Society for Music Information Retrieval.
31.
WangSiying.2017. Computational Methods for the Alignment and Score-Informed Transcription of Piano Music. Doctoral Dissertation . London: Queen Mary University of London.
32.
WeissChristof.2017. “Computational Methods for Tonality-Based Style Analysis of Classical Music Audio Recordings. ” (Doctoral dissertation
).
Ilmenau: Technische Universität Ilmenau.
33.
WeissChristof, MauchMhattias, DixonSimon, and MullerMeinard. 2018. “Investigating Style Evolution of Western Classical Music: A Computational Approach. ” Musicae Scientiae 23 (4): 486–507. doi: 10.1177/1029864918757595.
34.
WeissChristof, and MullerMeinard. 2015. Tonal Complexity Features for Style Classification of Classical Music. ” In
IEEE International Conference on Acoustics, Speech and Signal Processing, 688–692. doi: 10.1109/ICASSP.2015.7178057
