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arXiv · 2609.29128

Bio-inspired efficient cyclostationary analysis in machine and underwater acoustic recordings

Thura Pyae Sone·Abishek Soti·Henry Zhong·Gregory Cohen·RunChun Mark Wang·Ying Xu
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Abstract

We propose a bio-inspired approach that uses the inner-hair-cell (IHC) response of the Cascade of Asymmetric Resonators with Fast-Acting Compression (CARFAC) model to efficiently extract cyclic modulation from acoustic signals. We further investigate the contribution of IHC processing by comparing the CARFAC-IHC response with the CARFAC basilar-membrane (BM) filtering. Furthermore, the CARFAC-IHC and CARFAC-BM approach are benchmarked against conventional FFT Accumulation Method (FAM), Integrated Cyclic Modulation Coherence (ICMC), and Detection of Envelope Modulation On Noise (DEMON) approaches using the Case Western Reserve University (CWRU) bearing dataset and a real ShipsEar work-vessel recording dataset. The results demonstrate reliable recovery of characteristic cyclic components while substantially reducing the computational burden of conventional cyclostationary analysis.

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Thura Pyae Sone, Abishek Soti, Henry Zhong, Gregory Cohen, RunChun Mark Wang, Ying Xu. 2026-09-24. Bio-inspired efficient cyclostationary analysis in machine and underwater acoustic recordings. https://arxiv.org/abs/2609.29128

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