Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting

Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting

In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses w...

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Veröffentlicht in:Frontiers in neuroscience 2016-11, Vol.10 (NOV), p.474-474
Hauptverfasser: Werner, Thilo, Vianello, Elisa, Bichler, Olivier, Garbin, Daniele, Cattaert, Daniel, Yvert, Blaise, De Salvo, Barbara, Perniola, Luca
Format: Artikel
Sprache:eng
Schlagworte:
Brain
Brain-Computer Interfaces
Computer applications
Data compression
Engineering Sciences
Firing pattern
Implants
Laboratories
Latency
Neural networks
neuromorphic computing
Neurons
Neuroscience
OxRAM
Power
Principal components analysis
Rehabilitation
Signal processing
Software
spike sorting
Spike timing-dependent plasticity
Spiking Neural network
Synaptic strength
Wireless networks
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Zusammenfassung:In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses whose low latency (
ISSN:1662-4548
1662-453X
1662-453X
DOI:10.3389/fnins.2016.00474