Autor:

Kasiński, Andrzej ; Ponulak, Filip

Współtwórca:

Korbicz, Józef - red.

Tytuł:

Comparison of supervised learning methods for spike time coding in spiking neural networks

Podtytuł:

Soft Computing in Control and Fault Diagnosis

Tytuł publikacji grupowej:

AMCS, Volume 16 (2006)

Temat i słowa kluczowe:

supervised learning ; spiking neural networks ; time coding ; temporal sequences of spikes

Abstract:

In this review we focus our attention on supervised learning methods for spike time coding in Spiking Neural Networks(SNNs). This study is motivated by recent experimental results regarding information coding in biological neural systems,which suggest that precise timing of individual spikes may be essential for efficient computation in the brain. We areconcerned with the fundamental question: What paradigms of neural temporal coding can be implemented with the recentlearning methods? In order to answer this question, we discuss various approaches to the learning task considered. Weshortly describe the particular learning algorithms and report the results of experiments. Finally, we discuss the properties,assumptions and limitations of each method. We complete this review with a comprehensive list of pointers to the literature.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2006

Typ zasobu:

artykuł

Strony:

101-113

Źródło:

AMCS, Volume 16, Number 1 (2006) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego