Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Poster Communications Year : 2013

Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals

Abstract

The simultaneous analysis of multiple recordings of neuronal electromagnetic activity is an important task requiring sophisticated and extremely noise robust techniques. A general goal is to find a representation of the similarities (e.g. repeating waveforms) as well as the differences (e.g. varying shape, latency, phase, or amplitude of waveforms) across the signals. Here, we present an extension to dictionary learning that explicitly accounts for small variations in latency and phase of atoms.
Fichier principal
Vignette du fichier
posterJADL.pdf (3.04 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01094663 , version 1 (05-01-2015)

Identifiers

  • HAL Id : hal-01094663 , version 1

Cite

Sebastian Hitziger, Maureen Clerc, Alexandre Gramfort, Sandrine Saillet, Christian G. Bénar, et al.. Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals. International Conference on Learning Representations 2013, May 2013, Phoenix, Arizona, United States. 2013. ⟨hal-01094663⟩
186 View
78 Download

Share

Gmail Facebook X LinkedIn More