کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
404524 | 677432 | 2010 | 4 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
To spike or not to spike: A probabilistic spiking neuron model
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: To spike or not to spike: A probabilistic spiking neuron model To spike or not to spike: A probabilistic spiking neuron model](/preview/png/404524.png)
چکیده انگلیسی
Spiking neural networks (SNN) are promising artificial neural network (ANN) models as they utilise information representation as trains of spikes, that adds new dimensions of time, frequency and phase to the structure and the functionality of ANN. The current SNN models though are deterministic, that restricts their applications for large scale engineering and cognitive modelling of stochastic processes. This paper proposes a novel probabilistic spiking neuron model (pSNM) and suggests ways of building pSNN for a wide range of applications including classification, string pattern recognition and associative memory. It also extends previously published computational neurogenetic models.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neural Networks - Volume 23, Issue 1, January 2010, Pages 16–19
Journal: Neural Networks - Volume 23, Issue 1, January 2010, Pages 16–19
نویسندگان
Nikola Kasabov,