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20202026
most citedDecomposing non-stationary signals with time-varying wave-shape functions

23 citations · 43 across the 9 of their papers we have counts for

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9 papers · 1 filter

eess.SP2026

Time-Varying Spiky Wave-Shape Functions for Non-Stationary Signal Decomposition

Marcelo A. Colominas, Hau-Tieng Wu

We propose a novel framework for decomposing nonstationary spiky signals. Unlike classical adaptive non-harmonic models, which represent signals as amplitude- and frequency-modulat…

eess.SP2025

Time-Frequency Filtering Meets Graph Clustering

Marcelo A. Colominas, Stefan Steinerberger, Hau-Tieng Wu

We show that the problem of identifying different signal components from a time-frequency representation can be equivalently phrased as a graph clustering problem: given a graph $G…

eess.SP2023★ 7 cited

Fully Adaptive Time-Varying Wave-Shape Model: Applications in Biomedical Signal Processing

Joaquin Ruiz, Gastón Schlotthauer, Leandro Vignolo +1

In this work, we propose a time-varying wave-shape extraction algorithm based on a modified version of the adaptive non-harmonic model for non-stationary signals. The model codifie…

eess.SP2023★ 10 cited

Wave-shape Function Model Order Estimation by Trigonometric Regression

Joaquin Ruiz, Marcelo A. Colominas

The adaptive non-harmonic (ANH) model is a powerful tool to compactly represent oscillating signals with time-varying amplitude and phase, and non-sinusoidal oscillating morphology…

eess.SP2023

Enhancing Missing Data Imputation of Non-stationary Signals with Harmonic Decomposition

Joaquin Ruiz, Hau-tieng Wu, Marcelo A. Colominas

Dealing with time series with missing values, including those afflicted by low quality or over-saturation, presents a significant signal processing challenge. The task of recoverin…

eess.SP2022

Unsupervised classification of the spectrogram zeros

Juan M. Miramont, François Auger, Marcelo A. Colominas +2

The zeros of the spectrogram have proven to be a relevant feature to describe the time-frequency structure of a signal, originated by the destructive interference between component…

eess.SP2022★ 2 cited

An iterative warping and clustering algorithm to estimate multiple wave-shape functions from a nonstationary oscillatory signal

Marcelo A. Colominas, Hau-Tieng Wu

Nonsinusoidal oscillatory signals are everywhere. In practice, the nonsinusoidal oscillatory pattern, modeled as a 1-periodic wave-shape function (WSF), might vary from cycle to cy…

eess.SP2022★ 1 cited

Instantaneous Frequency Estimation In Multi-Component Signals Using Stochastic EM Algorithm

Quentin Legros, Dominique Fourer, Sylvain Meignen +1

This paper addresses the problem of estimating the modes of an observed non-stationary mixture signal in the presence of an arbitrary distributed noise. A novel Bayesian model is i…

eess.SP2020★ 23 cited

Decomposing non-stationary signals with time-varying wave-shape functions

Marcelo A. Colominas, Hau-Tieng Wu

Modern time series are usually composed of multiple oscillatory components, with time-varying frequency and amplitude contaminated by noise. The signal processing mission is furthe…