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Time-Frequency Representation Based on an Adaptive Short-Time Fourier Transform

2010/06/18 by Jingang Zhong, Yu Huang · 3 citations
Computer Science · Engineering · #Advanced Electrical Measurement Techniques #Image and Signal Denoising Methods #Machine Fault Diagnosis Techniques

paper · doi:10.1109/tsp.2010.2053028

openalex publication_date 2010/06/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/15

Abstract

In this paper, a new concise algorithm about time-frequency representation (TFR) based on an adaptive short-time Fourier transform (ASTFT) is presented. In this algorithm, the analysis window width is equal to the local stationary length which is measured by the instantaneous frequency gradient (IFG) of the signal. And the instantaneous frequency (IF) of the signal is obtained by detecting the ridge of wavelet transform (WT). The ASTFT provides much better performance than conventional TFR algorithms. Furthermore, the algorithm is simpler and more computational efficient than some of other adaptive TFR algorithms proposed previously. Several examples are presented to illustrate its behavior on different kinds of signals and demonstrate its validity.

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