語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Persistent homology and discrete Fou...
~
Callet-Feltz, Victoria.
FindBook
Google Book
Amazon
博客來
Persistent homology and discrete Fourier transform = an application to topological musical data analysis /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Persistent homology and discrete Fourier transform/ by Victoria Callet-Feltz.
其他題名:
an application to topological musical data analysis /
作者:
Callet-Feltz, Victoria.
出版者:
Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:
xv, 230 p. :ill. (some col.), digital ;24 cm.
內容註:
1 Introduction -- Part I The two-dimensional Discrete Fourier Transform -- 2 The DFT for modeling basic musical structures -- 3 Generalization of theoretical results -- Part II Persistent homology on musical bars -- 4 Mathematical background -- 5 Musical scores and filtration -- Part III Musical applications -- 6 The DFT as a metric on the set of notes and chord -- 7 Harmonization of Pop songs -- 8 Classification of musical style -- 9 A different approach: the Hausdorff distance -- 10 Conclusion and perspectives for future research.
Contained By:
Springer Nature eBook
標題:
Music - Mathematics. -
電子資源:
https://doi.org/10.1007/978-3-031-82236-0
ISBN:
9783031822360
Persistent homology and discrete Fourier transform = an application to topological musical data analysis /
Callet-Feltz, Victoria.
Persistent homology and discrete Fourier transform
an application to topological musical data analysis /[electronic resource] :by Victoria Callet-Feltz. - Cham :Springer Nature Switzerland :2025. - xv, 230 p. :ill. (some col.), digital ;24 cm. - Computational music science,1868-0313. - Computational music science..
1 Introduction -- Part I The two-dimensional Discrete Fourier Transform -- 2 The DFT for modeling basic musical structures -- 3 Generalization of theoretical results -- Part II Persistent homology on musical bars -- 4 Mathematical background -- 5 Musical scores and filtration -- Part III Musical applications -- 6 The DFT as a metric on the set of notes and chord -- 7 Harmonization of Pop songs -- 8 Classification of musical style -- 9 A different approach: the Hausdorff distance -- 10 Conclusion and perspectives for future research.
This book proposes contributions to various problems in the field of topological analysis of musical data: the objects studied are scores represented symbolically by MIDI files, and the tools used are the discrete Fourier transform and persistent homology. The manuscript is divided into three parts: the first two are devoted to the study of the aforementioned mathematical objects and the implementation of the model. More precisely, the notion of DFT introduced by Lewin is generalized to the case of dimension two, by making explicit the passage of a musical bar from a piece to a subset of Z/tZ×Z/pZ, which leads naturally to a notion of metric on the set of musical bars by their Fourier coefficients. This construction gives rise to a point cloud, to which the filtered Vietoris-Rips complex is associated, and consequently a family of barcodes given by persistent homology. This approach also makes it possible to generalize classical results such as Lewin's lemma and Babitt's Hexachord theorem. The last part of this book is devoted to musical applications of the model: the first experiment consists in extracting barcodes from artificially constructed scores, such as scales or chords. This study leads naturally to song harmonization process, which reduces a song to its melody and chord grid, thus defining the notions of graph and complexity of a piece. Persistent homology also lends itself to the problem of automatic classification of musical style, which will be treated here under the prism of symbolic descriptors given by statistics calculated directly on barcodes. Finally, the last application proposes a encoding of musical bars based on the Hausdorff distance, which leads to the study of musical textures. The book is addressed to graduate students and researchers in mathematical music theory and music information research, but also at researchers in other fields, such as applied mathematicians and topologists, who want to learn more about mathematical music theory or music information research.
ISBN: 9783031822360
Standard No.: 10.1007/978-3-031-82236-0doiSubjects--Topical Terms:
2179507
Music
--Mathematics.
LC Class. No.: ML3800
Dewey Class. No.: 780.0519
Persistent homology and discrete Fourier transform = an application to topological musical data analysis /
LDR
:03708nmm a2200361 a 4500
001
2409773
003
DE-He213
005
20250601130241.0
006
m d
007
cr nn 008maaau
008
260204s2025 sz s 0 eng d
020
$a
9783031822360
$q
(electronic bk.)
020
$a
9783031822353
$q
(paper)
024
7
$a
10.1007/978-3-031-82236-0
$2
doi
035
$a
978-3-031-82236-0
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
ML3800
072
7
$a
PBW
$2
bicssc
072
7
$a
AVA
$2
bicssc
072
7
$a
MAT003000
$2
bisacsh
072
7
$a
PBW
$2
thema
072
7
$a
AVA
$2
thema
082
0 4
$a
780.0519
$2
23
090
$a
ML3800
$b
.C157 2025
100
1
$a
Callet-Feltz, Victoria.
$3
3783186
245
1 0
$a
Persistent homology and discrete Fourier transform
$h
[electronic resource] :
$b
an application to topological musical data analysis /
$c
by Victoria Callet-Feltz.
260
$a
Cham :
$b
Springer Nature Switzerland :
$b
Imprint: Springer,
$c
2025.
300
$a
xv, 230 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Computational music science,
$x
1868-0313
505
0
$a
1 Introduction -- Part I The two-dimensional Discrete Fourier Transform -- 2 The DFT for modeling basic musical structures -- 3 Generalization of theoretical results -- Part II Persistent homology on musical bars -- 4 Mathematical background -- 5 Musical scores and filtration -- Part III Musical applications -- 6 The DFT as a metric on the set of notes and chord -- 7 Harmonization of Pop songs -- 8 Classification of musical style -- 9 A different approach: the Hausdorff distance -- 10 Conclusion and perspectives for future research.
520
$a
This book proposes contributions to various problems in the field of topological analysis of musical data: the objects studied are scores represented symbolically by MIDI files, and the tools used are the discrete Fourier transform and persistent homology. The manuscript is divided into three parts: the first two are devoted to the study of the aforementioned mathematical objects and the implementation of the model. More precisely, the notion of DFT introduced by Lewin is generalized to the case of dimension two, by making explicit the passage of a musical bar from a piece to a subset of Z/tZ×Z/pZ, which leads naturally to a notion of metric on the set of musical bars by their Fourier coefficients. This construction gives rise to a point cloud, to which the filtered Vietoris-Rips complex is associated, and consequently a family of barcodes given by persistent homology. This approach also makes it possible to generalize classical results such as Lewin's lemma and Babitt's Hexachord theorem. The last part of this book is devoted to musical applications of the model: the first experiment consists in extracting barcodes from artificially constructed scores, such as scales or chords. This study leads naturally to song harmonization process, which reduces a song to its melody and chord grid, thus defining the notions of graph and complexity of a piece. Persistent homology also lends itself to the problem of automatic classification of musical style, which will be treated here under the prism of symbolic descriptors given by statistics calculated directly on barcodes. Finally, the last application proposes a encoding of musical bars based on the Hausdorff distance, which leads to the study of musical textures. The book is addressed to graduate students and researchers in mathematical music theory and music information research, but also at researchers in other fields, such as applied mathematicians and topologists, who want to learn more about mathematical music theory or music information research.
650
0
$a
Music
$x
Mathematics.
$3
2179507
650
0
$a
Homology theory.
$3
555733
650
0
$a
Fourier transformations.
$3
533900
650
1 4
$a
Mathematics in Music.
$3
1619562
650
2 4
$a
Applications of Mathematics.
$3
890893
650
2 4
$a
Music.
$3
516178
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
830
0
$a
Computational music science.
$3
2111485
856
4 0
$u
https://doi.org/10.1007/978-3-031-82236-0
950
$a
Computer Science (SpringerNature-11645)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9515271
電子資源
11.線上閱覽_V
電子書
EB ML3800
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入