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Titlebook: Artificial Neural Networks - ICANN 2010; 20th International C Konstantinos Diamantaras,Wlodek Duch,Lazaros S. Il Conference proceedings 201

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Investigation of Brain-Computer Interfaces That Apply Sound-Evoked Event-Related Potentialsection was indicated by the experimenter, although the direction of the sound cue emitted during the trials was not necessarily the target direction. Changes in brain activity were measured using an electroencephalogram (EEG) . Experimental results showed that prominent excitations in EEG signals we
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0302-9743 sist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation funct978-3-642-15818-6978-3-642-15819-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Fiber Crystal Growth from the Melt 25°C , being supplied at the minimal supply voltage .= 1.7.. The temperature coefficient of the reference voltage is 8.5. /°. , while the line sensitivity is 0.7. /. for a supply voltage between 1.7. and 7..
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Absorption from the Human Colonns (except for pitch), for the typical motion amplitudes encountered in FMRI studies. Results with an actual time series suggest that the proposed method is suited to the problem of prospective (in frame) FMRI registration, although brain activation must be simulated, and learned, by the NN.
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Wavelength Division Multiplexing (WDM), dendritic spike. We show that during such pairing conditions in the absence of inhibition a symmetric STDP profile with a distinct positive LTP region is evident at 10-30ms interstimulus interval and flat LTD tails at all other interstimulus intervals. The symmetry is preserved at all burst intersp
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Conference proceedings 2010ng structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation funct
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Conference proceedings 2010h- saloniki, Greece during September 15–18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually s
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Modelling Power Output at Nuclear Power Plant by Neural Networks input signals and neurons in hidden-layer are found to make possible prediction of idle power process signal. It is mainly concentrated on algorithms on input signal selection and finding the optimal model for one-step ahead prediction.
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