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- Time–frequency analysis for music signals is one of the applications of time–frequency analysis. Musical sound can be more complicated than human vocal sound, occupying a wider band of frequency. Music signals are time-varying signals; while the classic Fourier transform is not sufficient to analyze them, time–frequency analysis is an efficient tool for such use. Time–frequency analysis is extended from the classic Fourier approach. Short-time Fourier transform (STFT), Gabor transform (GT) and Wigner distribution function (WDF) are famous time–frequency methods, useful for analyzing music signals such as notes played on a piano, a flute or a guitar. (en)
- 音樂信號時頻分析（英語：Time–frequency analysis for music signals）為時頻分析應用之一。音樂聲音可以比人聲更加複雜，佔用更寬的頻帶，音樂信號為隨時間變化的信號，只使用單純的傅立葉變換無法清楚分析，所以利用時間-頻率分析做更有效的分析工具。時頻分析為傳統傅立葉變換延伸版。短時距傅立葉變換、加伯轉換與維格納分佈最被廣泛使用之時頻分析方法，對於分析音樂信號也相當管用。 (zh)
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- C-E-G, C-E-A, D-F-A chords played on an instrument. (en)
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- Time–frequency analysis for music signals is one of the applications of time–frequency analysis. Musical sound can be more complicated than human vocal sound, occupying a wider band of frequency. Music signals are time-varying signals; while the classic Fourier transform is not sufficient to analyze them, time–frequency analysis is an efficient tool for such use. Time–frequency analysis is extended from the classic Fourier approach. Short-time Fourier transform (STFT), Gabor transform (GT) and Wigner distribution function (WDF) are famous time–frequency methods, useful for analyzing music signals such as notes played on a piano, a flute or a guitar. (en)
- 音樂信號時頻分析（英語：Time–frequency analysis for music signals）為時頻分析應用之一。音樂聲音可以比人聲更加複雜，佔用更寬的頻帶，音樂信號為隨時間變化的信號，只使用單純的傅立葉變換無法清楚分析，所以利用時間-頻率分析做更有效的分析工具。時頻分析為傳統傅立葉變換延伸版。短時距傅立葉變換、加伯轉換與維格納分佈最被廣泛使用之時頻分析方法，對於分析音樂信號也相當管用。 (zh)
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- Time–frequency analysis for music signals (en)
- 音樂訊號之時頻分析 (zh)
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