Raga Analysis Using Entropy

Soubhik Chakraborty; Guerino Mazzola; Swarima Tewari; Moujhuri Patra

doi:10.1007/978-3-319-11472-9_6

Raga Analysis Using Entropy

Soubhik Chakraborty, Guerino Mazzola, Swarima Tewari, Moujhuri Patra

Music (Twin Cities)

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

If P(E) is the probability of an event, the information content of the event E is defined as I(E) = −log₂(P(E)). Events with lower probability will signal higher information content when they occur. The probability of a raga note, and hence its information content, depends on the raga concerned. The important raga notes will obviously be having higher probabilities. On the other hand, a weak note in a raga cannot be thrown away either for it would be carrying more surprise! The strength of entropy analysis lies here (entropy is the mean information content of a random variable).

Original language	English (US)
Title of host publication	Computational Music Science
Publisher	Springer Nature
Pages	65-68
Number of pages	4
DOIs	https://doi.org/10.1007/978-3-319-11472-9_6
State	Published - 2014

Publication series

Name	Computational Music Science
ISSN (Print)	1868-0305
ISSN (Electronic)	1868-0313

Bibliographical note

Publisher Copyright:
© 2014, Springer International Publishing Switzerland.

Keywords

Discrete Random Variable
Information Content
Negative Information
Small Positive Number
Zero Probability

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10.1007/978-3-319-11472-9_6

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title = "Raga Analysis Using Entropy",

abstract = "If P(E) is the probability of an event, the information content of the event E is defined as I(E) = −log2(P(E)). Events with lower probability will signal higher information content when they occur. The probability of a raga note, and hence its information content, depends on the raga concerned. The important raga notes will obviously be having higher probabilities. On the other hand, a weak note in a raga cannot be thrown away either for it would be carrying more surprise! The strength of entropy analysis lies here (entropy is the mean information content of a random variable).",

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doi = "10.1007/978-3-319-11472-9_6",

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AU - Chakraborty, Soubhik

AU - Mazzola, Guerino

AU - Tewari, Swarima

AU - Patra, Moujhuri

PY - 2014

Y1 - 2014

N2 - If P(E) is the probability of an event, the information content of the event E is defined as I(E) = −log2(P(E)). Events with lower probability will signal higher information content when they occur. The probability of a raga note, and hence its information content, depends on the raga concerned. The important raga notes will obviously be having higher probabilities. On the other hand, a weak note in a raga cannot be thrown away either for it would be carrying more surprise! The strength of entropy analysis lies here (entropy is the mean information content of a random variable).

AB - If P(E) is the probability of an event, the information content of the event E is defined as I(E) = −log2(P(E)). Events with lower probability will signal higher information content when they occur. The probability of a raga note, and hence its information content, depends on the raga concerned. The important raga notes will obviously be having higher probabilities. On the other hand, a weak note in a raga cannot be thrown away either for it would be carrying more surprise! The strength of entropy analysis lies here (entropy is the mean information content of a random variable).

KW - Discrete Random Variable

KW - Information Content

KW - Negative Information

KW - Small Positive Number

KW - Zero Probability

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BT - Computational Music Science

PB - Springer Nature

ER -

Raga Analysis Using Entropy

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