# Ridge detection for nonstationary multicomponent signals with time-varying wave-shape functions and its applications

arXiv: https://arxiv.org/abs/2309.06673 · HTML: https://mlsanity.com/paper/2309.06673/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Sep 2023.

## Built on by (most cited first, 1 of 1)

- [Wavelet Mixture of Experts for Time Series Forecasting](https://mlsanity.com/paper/2508.08825/) (2025)

## Abstract (arXiv)

We introduce a novel ridge detection algorithm for time-frequency (TF) analysis, particularly tailored for intricate nonstationary time series encompassing multiple non-sinusoidal oscillatory components. The algorithm is rooted in the distinctive geometric patterns that emerge in the TF domain due to such non-sinusoidal oscillations. We term this method textitshape-adaptive mode decomposition-based multiple harmonic ridge detection (textsfSAMD-MHRD). A swift implementation is available when supplementary information is at hand. We demonstrate the practical utility of textsfSAMD-MHRD through its application to a real-world challenge. We employ it to devise a cutting-edge walking activity detection algorithm, leveraging accelerometer signals from an inertial measurement unit across diverse body locations of a moving subject.