22 citations · 41 across the 8 of their papers we have counts for
10 papers
Time-warping estimation via stationarity-based learning of the de-warped signal
Corentin Presvôts, Adrien Meynard
Time-warping estimation is a fundamental problem in signal processing with applications in bioacoustics, radar, and biomedical analysis. This paper introduces a Time-Warping Estima…
Inverse Laplace Transform for Dynamic Light Scattering: Impact of Regularization
Pierre Pajuelo, Stéphane G. Roux, Adrien Meynard +3
Dynamic Light Scattering (DLS) analyzes particle dynamics from the autocorrelation functions of scattered light intensity, yet extracting accurate relaxation time distributions fro…
Consistent Spectrogram Separation from Nonstationary Mixture
Adrien Meynard, Ama Marina Kreme
We present a spectrogram separation method tailored for mixtures comprising two nonstationary components. By exploiting the unique characteristics of their time-frequency represent…
Synthesis-based time-scale transforms for non-stationary signals
Adrien Meynard, Bruno Torrésani
This paper deals with the modeling of non-stationary signals, from the point of view of signal synthesis. A class of random, non-stationary signals, generated by synthesis from a r…
Predicting Trust Using Automated Assessment of Multivariate Interactional Synchrony
Adrien Meynard, Gayan Seneviratna, Elliot Doyle +3
Diverse disciplines are interested in how the coordination of interacting agents' movements, emotions, and physiology over time impacts social behavior. Here, we describe a new mul…
An Efficient Forecasting Approach to Reduce Boundary Effects in Real-Time Time-Frequency Analysis
Adrien Meynard, Hau-Tieng Wu
Time-frequency (TF) representations of time series are intrinsically subject to the boundary effects. As a result, the structures of signals that are highlighted by the representat…
Time-scale synthesis for locally stationary signals
Adrien Meynard, Bruno Torrésani
We develop a timescale synthesis-based probabilistic approach for the modeling of locally stationary signals. Inspired by our previous work, the model involves zero-mean, complex G…
Joint nonstationary blind source separation and spectral analysis
Adrien Meynard
We address a nonstationary blind source separation (BSS) problem. The model includes both nonstationary sources and mixing. Therefore, we introduce an algorithm for joint BSS and e…
Spectral analysis for nonstationary audio
Adrien Meynard, Bruno Torrésani
A new approach for the analysis of nonstationary signals is proposed, with a focus on audio applications. Following earlier contributions, nonstationarity is modeled via stationari…
Convex Optimization approach to signals with fast varying instantaneous frequency
Matthieu Kowalski, Adrien Meynard, Hau-tieng Wu
Motivated by the limitation of analyzing oscillatory signals composed of multiple components with fast-varying instantaneous frequency, we approach the time-frequency analysis prob…