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A Study of Evolutionary Trends of Classical Music Works Based on Data Mining

Nov 18, 2024

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Applied Mathematics and Nonlinear Sciences

Volume 9 (2024): Issue 1 (January 2024)

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Published Online: Nov 18, 2024

Received: Jun 23, 2024

Accepted: Oct 12, 2024

DOI: https://doi.org/10.2478/amns-2024-3318

Keywords
<kwd>PCP features</kwd>, <kwd>MFCC algorithm</kwd>, <kwd>Bidirectional LSTM</kwd>, <kwd>Self-attention mechanism</kwd>, <kwd>Classical music works</kwd>

© 2024 Yeye Li., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Li, Yeye

College of Music, Sichuan University of Light Chemical TechnologyZigong, China

Language:: English

Publication timeframe:: 1 times per year
Journal Subjects:: Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other

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