# On the Practical Use of Blaschke Decomposition in Nonstationary Signal Analysis

arXiv: https://arxiv.org/abs/2508.10861 · HTML: https://mlsanity.com/paper/2508.10861/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Aug 2025.

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

- [The Singularity Space: A Generative Diffusion Framework for Signal Representation](https://mlsanity.com/paper/2607.10930/) (2026)

## Abstract (arXiv)

The Blaschke decomposition-based algorithm, em Phase Dynamics Unwinding (PDU), possesses several attractive theoretical properties, including fast convergence, effective decomposition, and multiscale analysis. However, its application to real-world signal decomposition tasks encounters notable challenges. In this work, we propose two techniques, divide-and-conquer via tapering and cumulative summation (cumsum), to handle complex trends and amplitude modulations and the mode-mixing caused by winding. The resulting method, termed em windowed PDU, enhances PDU's performance in practical decomposition tasks. We validate our approach through both simulated and real-world signals, demonstrating its effectiveness across diverse scenarios.