MMSDNAJun 29, 2016

Minimum-latency Time-frequency Analysis Using Asymmetric Window Functions

arXiv:1606.09047v15 citations
Originality Incremental advance
AI Analysis

This work addresses latency reduction in time-frequency representations for applications like real-time signal processing, though it appears incremental as it builds on existing methods like SST and RM.

The authors tackled the problem of minimizing latency in time-frequency analysis for real-time dynamics retrieval by proposing a systematic method to construct asymmetric windows from symmetric ones, achieving a smaller intrinsic latency in synchrosqueezing transform as demonstrated in music onset detection.

We study the real-time dynamics retrieval from a time series via the time-frequency (TF) analysis with the minimal latency guarantee. While different from the well-known intrinsic latency definition in the filter design, a rigorous definition of intrinsic latency for different time-frequency representations (TFR) is provided, including the short time Fourier transform (STFT), synchrosqeezing transform (SST) and reassignment method (RM). To achieve the minimal latency, a systematic method is proposed to construct an asymmetric window from a well-designed symmetric one based on the concept of minimum-phase, if the window satisfies some weak conditions. We theoretically show that the TFR determined by SST with the constructed asymmetric window does have a smaller intrinsic latency. Finally, the music onset detection problem is studied to show the strength of the proposed algorithm.

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