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NPL
2000
146views more  NPL 2000»
13 years 7 months ago
Competitive and Temporal Inhibition Structures with Spiking Neurons
The paper describes the implementation of competitive neural structures based on a spiking neural model that includes multiplicative or shunting synapses enabling non-saturated sta...
Eduardo Ros Vidal, Francisco J. Pelayo, P. Martin-...
CDC
2009
IEEE
108views Control Systems» more  CDC 2009»
14 years 6 days ago
The parabigeminal nucleus as a recursive estimator
— The parabigeminal nucleus (PBN) is known to estimate the retinal position error (RPE) of an intended target. Recently it has been discovered that PBN activity continues to enco...
Rui Ma, Todd P. Coleman, Joseph G. Malpeli
IJCNN
2008
IEEE
14 years 1 months ago
Biologically realizable reward-modulated hebbian training for spiking neural networks
— Spiking neural networks have been shown capable of simulating sigmoidal artificial neural networks providing promising evidence that they too are universal function approximat...
Silvia Ferrari, Bhavesh Mehta, Gianluca Di Muro, A...
ESANN
2004
13 years 9 months ago
Input arrival-time-dependent decoding scheme for a spiking neural network
Spiking neurons model a type of biological neural system where information is encoded with spike times. In this paper, a new method for decoding input spikes according to their abs...
Hesham H. Amin, Robert H. Fujii
ISCAS
2008
IEEE
84views Hardware» more  ISCAS 2008»
14 years 1 months ago
Pulse-based signal compression for implanted neural recording systems
— Today’s implanted neural systems are bound by tight constraints on power and communication bandwidth. Most conventional ADC-based approaches fall into two categories. Either ...
John G. Harris, Jose C. Principe, Justin C. Sanche...