TH1.SC4.6
NEURAL NETWORKS FOR PERIODIC SIGNALS IN TIME AND FREQUENCY DOMAINS – THE ADVANTAGE OF A SPECTRAL STRIDE CNN
Nico Herwig, Pietro Borghesani, UNSW Sydney, Australia; Wenyi Wang, Defence Science and Technology Group, Australia; Jerome Antoni, Univ Lyon, INSA Lyon, France
Session:
TH1.SC4: Science Data with Hidden Periodic Structure - New Perspectives Lecture
Track:
Special Sessions
Location:
Saint Clair 4
Presentation Time:
Thu, 29 Aug, 12:10 - 12:30 France Time (UTC +1)
Session Co-Chairs:
Antonio Napolitano, University of Napoli Parthenope and Agnieszka Wyłomańska, Wrocław University of Science and Technology
Presentation
Discussion
Resources
No resources available.
Session TH1.SC4
TH1.SC4.1: Identification of quasi-periodically varying systems using the local basis function approach
Artur Gancza, Maciej Niedzwiecki, Gdansk University of Technology, Poland
TH1.SC4.2: ERRORS-IN-VARIABLES-BASED METHODOLOGY OF ESTIMATION AND TESTING FOR INFINITE-VARIANCE PERIODIC AUTOREGRESSIVE MODELS WITH ADDITIVE NOISE
Wojciech Żuławiński, Agnieszka Wyłomańska, Wrocław University of Science and Technology, Poland
TH1.SC4.3: Error-Related Potential classification through the use of the detectivity parameter
Adriana Lucchese, Gianluca D'Elia, Riccardo Rubini, Marco Cocconcelli, University of Modena and Reggio Emilia, Italy
TH1.SC4.4: DE-WARPING ALGORITHMS FOR OSCILLATORY ALMOST-CYCLOSTATIONARY PROCESSES
Antonio Napolitano, University of Napoli Parthenope, Italy
TH1.SC4.5: Order tracking on cyclic kurtosis for damage detection of bearing faults
Alexandre Mauricio, Zhen Li, Mahsa Yazdanianasr, Konstantinos Gryllias, KU Leuven, Belgium
TH1.SC4.6: NEURAL NETWORKS FOR PERIODIC SIGNALS IN TIME AND FREQUENCY DOMAINS – THE ADVANTAGE OF A SPECTRAL STRIDE CNN
Nico Herwig, Pietro Borghesani, UNSW Sydney, Australia; Wenyi Wang, Defence Science and Technology Group, Australia; Jerome Antoni, Univ Lyon, INSA Lyon, France