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» On the use of spiking neural network for EEG classification
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ICANN
2007
Springer
13 years 10 months ago
Solving Selected Classification Problems in Bioinformatics Using Multilayer Neural Network Based on Multi-Valued Neurons (MLMVN)
A multilayer neural network based on multi-valued neurons (MLMVN) is a new powerful tool for solving classification, recognition and prediction problems. This network has a number ...
Igor N. Aizenberg, Jacek M. Zurada
BIOSYSTEMS
2007
111views more  BIOSYSTEMS 2007»
13 years 8 months ago
Event-driven simulation of neural population synchronization facilitated by electrical coupling
Most neural communication and processing tasks are driven by spikes. This has enabled the application of the event-driven simulation schemes. However the simulation of spiking neu...
Richard R. Carrillo, Eduardo Ros, Boris Barbour, C...
HCI
2009
13 years 6 months ago
Mind-Mirror: EEG-Guided Image Evolution
Abstract. We propose a brain-computer interface (BCI) system for evolving images in realtime based on subject feedback derived from electroencephalography (EEG). The goal of this s...
Nima Bigdely Shamlo, Scott Makeig
ESANN
2008
13 years 10 months ago
Visual focus with spiking neurons
Attentional focusing can be implemented with a neural field [1], which uses a discharge rate code. As an alternative, we propose in the present work an implementation based on spik...
Sylvain Chevallier, Philippe Tarroux
ISNN
2010
Springer
14 years 1 months ago
Applications of Second Order Blind Identification to High-Density EEG-Based Brain Imaging: A Review
In the context of relating specific brain functions to specific brain structures, second-order blind identification (SOBI) is one of the blind source separation algorithms that hav...
Akaysha Tang