Acoustic Signal Processing Revisited: ExploringHilbert-Huang Transform and the Challenge ofCross-Term Errors

سال انتشار: 1403
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 77

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ISAV14_042

تاریخ نمایه سازی: 15 بهمن 1403

چکیده مقاله:

Numerous comprehensive studies have investigated the effectiveness of joint time-frequency transformations for analyzing non-stationary time series data. The primary objective of these investigations is to improve accuracy in both time and frequency domains, which is crucial for a wide range of applications. These methods have demonstrated significant efficacy in various research fields, particularly in audio and acoustic signal processing. Despite their success, several challenges persist, such as the occurrence of cross-term errors. This paper presents a comparative analysis of two prominent time-frequency analysis methods: The Short-Time Fourier Transform (STFT) and the Hilbert-Huang Transform (HHT). We employ three acoustic signal types, drawn from industrial applications, music, and audio processing, to evaluate the performance of each method. Our findings reveal that the STFT outperforms the HHT, providing more accurate results across all tested signal types. Notably, the HHT in-troduces a higher risk of cross-term errors, which can compromise the clarity and usability of the analyzed data.

نویسندگان

Javad Isavand

School of Mechatronics Engineering, Harbin Institute of Technology, Harbin, China.

Andrew Peplow

Principal Acoustic Consultant, Hawkins & Associates, Cambridge, England.

Jihong Yan

School of Mechatronics Engineering, Harbin Institute of Technology, Harbin, China.