منابع مشابه
SPAN: spike pattern association neuron for learning spatio-temporal sequences
Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatiotemporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN — a spiking neuron that is able to learn associations of arbitrary spike trains...
متن کاملSpan: Spike Pattern Association Neuron for Learning Spatio-Temporal Spike Patterns
Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN - a spiking neuron that is able to learn associations of arbitrary spike train...
متن کاملCompetitive STDP-Based Spike Pattern Learning
Recently it has been shown that a repeating arbitrary spatiotemporal spike pattern hidden in equally dense distracter spike trains can be robustly detected and learned by a single neuron equipped with spike-timing-dependent plasticity (STDP) (Masquelier, Guyonneau, & Thorpe, 2008). To be precise, the neuron becomes selective to successive coincidences of the pattern. Here we extend this scheme ...
متن کاملSpatio-temporal Spike Pattern Classification in Neuromorphic Systems
Spike-based neuromorphic electronic architectures offer an attractive solution for implementing compact efficient sensory-motor neural processing systems for robotic applications. Such systems typically comprise event-based sensors and multi-neuron chips that encode, transmit, and process signals using spikes. For robotic applications, the ability to sustain real-time interactions with the envi...
متن کاملTemporal pattern identification using spike-timing dependent plasticity
This paper addresses the question of the functional role of the dual application of positive and negative Hebbian time dependent plasticity rules, in the particular framework of reinforcement learning tasks. Our simulations take place in a recurrent network of spiking neurons with inhomogeneous synaptic weights. The network spontaneously displays a self-sustained activity. A Spike-Timing Depend...
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ژورنال
عنوان ژورنال: BMC Neuroscience
سال: 2008
ISSN: 1471-2202
DOI: 10.1186/1471-2202-9-s1-p4