Evolving small spiking neural networks to work as state machines for temporal pattern recognition
نویسندگان
چکیده
منابع مشابه
Dynamic evolving spiking neural networks for on-line spatio- and spectro-temporal pattern recognition.
On-line learning and recognition of spatio- and spectro-temporal data (SSTD) is a very challenging task and an important one for the future development of autonomous machine learning systems with broad applications. Models based on spiking neural networks (SNN) have already proved their potential in capturing spatial and temporal data. One class of them, the evolving SNN (eSNN), uses a one-pass...
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Nervous systems of biological organisms use temporal patterns of spikes to encode sensory input, but the mechanisms that underlie the recognition of such patterns are unclear. In the present work, we explore how networks of spiking neurons can be evolved to recognize temporal input patterns without being able to adjust signal conduction delays. We evolve the networks with GReaNs, an artificial ...
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ژورنال
عنوان ژورنال: BMC Neuroscience
سال: 2015
ISSN: 1471-2202
DOI: 10.1186/1471-2202-16-s1-p238