7 citations · 11 across the 7 of their papers we have counts for
7 papers
Iteration over event space in time-to-first-spike spiking neural networks for Twitter bot classification
Mateusz Pabian, Dominik Rzepka, Mirosław Pawlak
This study proposes a framework that extends existing time-coding time-to-first-spike spiking neural network (SNN) models to allow processing information changing over time. We exp…
Pseudo-inverse reconstruction of bandlimited signals from nonuniform generalized samples with orthogonal kernels
Nguyen T. Thao, Dominik Rzepka, Marek Miskowicz
Contrary to the traditional pursuit of research on nonuniform sampling of bandlimited signals, the objective of the present paper is not to find sampling conditions that permit per…
Bayes Risk Consistency of Nonparametric Classification Rules for Spike Trains Data
Mirosław Pawlak, Mateusz Pabian, Dominik Rzepka
Spike trains data find a growing list of applications in computational neuroscience, imaging, streaming data and finance. Machine learning strategies for spike trains are based on…
POCS-based framework of signal reconstruction from generalized non-uniform samples
Nguyen T. Thao, Dominik Rzepka, Marek Miśkowicz
We formalize the use of projections onto convex sets (POCS) for the reconstruction of signals from non-uniform samples in their highest generality. This covers signals in any Hilbe…
Supervised Training of Siamese Spiking Neural Networks with Earth Mover's Distance
Mateusz Pabian, Dominik Rzepka, Mirosław Pawlak
This study adapts the highly-versatile siamese neural network model to the event data domain. We introduce a supervised training framework for optimizing Earth Mover's Distance (EM…
Bandlimited signal reconstruction from leaky integrate-and-fire encoding using POCS
Nguyen T. Thao, Dominik Rzepka, Marek Miśkowicz
Leaky integrate-and-fire (LIF) encoding is a model of neuron transfer function in biology that has recently attracted the attention of the signal processing and neuromorphic comput…
Time encoding of bandlimited signals: reconstruction by pseudo-inversion and time-varying multiplierless FIR filtering
Nguyen T. Thao, Dominik Rzepka
We propose an entirely redesigned framework of bandlimited signal reconstruction for the time encoding machine (TEM) introduced by Lazar and Tóth. As the encoding part of TEM consi…