Warianty tytułu
Mechanizmy przetwarzania informacji i uczenia w impulsowych sieciach neuronowych
Języki publikacji
Abstrakty
The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also heen adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many systems, neural code is founded on the timing of individual action potentials. The finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons. We focus, in particular, on various models for information coding, synaptic plasticity and learning in spiking networks. Finally, we discuss some real-life applications of spiking models.
Jednym z podstawowych paradygmatów obowiązująych przez wiele lat w neurobiologii była koncepcja kodowania informacji za pomocą średniej częstotliwości impulsów nerwowych. Koncepcja ta została zaadoptowana także w teorii sztucznych sieci neuronowych. Aktualne badania w zakresie neurofizjologii wskazują jednak na istotną rolę indywidualnych impulsów nerwowych w kodowaniu informacji. Odkrycie to dało początek nowej klasie sztucznych sieci neuronowych - tak zwanym sieciom impulsowym. W artykule przedstawione są podstawowe właściwości neuronów impulsowych. Szczególna uwaga poświęcona jest mechanizmom przetwarzania informacji oraz modelom plastyczności synaptycznej i uczenia w sieciach impulsowych. Artykuł zakończony jest dyskusją na temat wybranych zastosowań sieci impulsowych w zadaniach inżynierskich oraz w neuromodelowaniu.
Rocznik
Tom
Strony
23-40
Opis fizyczny
Bibliogr. 81 poz., rys., wykr.
Twórcy
autor
autor
- Poznan University of Technology, Institute of Control and Information Engineering, ul. Piotrowo 3a, 60-965 Poznań, Poland, Filip.Ponulak@put.poznan.pl
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Bibliografia
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bwmeta1.element.baztech-article-PWA9-0045-0002