RT journal article
T1 WiN-GUI: A graphical tool for neuron-based encoding
A1 Müller-Cleve, Simon F.
A1 Quintana Velázquez, Fernando Manuel
A1 Fra, Vittorio
A1 Galindo Riaño, Pedro Luis
A1 Pérez Peña, Fernando
A1 Urgese, Gianvito
A1 Bartolozzi, Chiara
A2 Ingeniería en AutomáticaElectrónica, Arquitectura y Redes de Computadores
A2 Ingeniería Informática
K1 Development tool
K1 Graphical user interface
K1 Neuromorphic
K1 Robotics
K1 Spike encoding
AB Neuromorphic computing relies on event-based, energy-efficient communication, inherently implying the need for conversion between real-valued (sensory) data and binary, sparse spiking representation. This is usually accomplished by using the real-valued data as current input to a spiking neuron model and tuning the neuron's parameters to match a desired – often biologically inspired – behavior. To support the investigation of neuron models and parameter combinations to identify suitable configurations for neuron-based encoding of sample-based data into spike trains we developed the WiN-GUI. Thanks to the generalized LIF model implemented by default, next to the LIF and Izhikevich neuron models, many spiking behaviors can be investigated out of the box offering the possibility of tuning biologically plausible responses to the input data. The GUI is provided open source and with documentation and is easy to extend with further neuron models and personalize with data analysis functions.
PB Elsevier B.V.
SN 2352-7110
YR 2024
FD 2024
LK http://hdl.handle.net/10498/33833
UL http://hdl.handle.net/10498/33833
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 10-may-2026