Artificial neural network with modulation of synaptic coefficients
- Authors: Nazarov M.N1
-
Affiliations:
- National Research University of Electronic Technology
- Issue: Vol 17, No 2 (2013)
- Pages: 58-71
- Section: Articles
- URL: https://journal-vniispk.ru/1991-8615/article/view/20817
- ID: 20817
Cite item
Abstract
The model of neural network based on artificial neuron with dynamic synaptic weights was constructed. As main model processes for changing the synaptic weights were chosen: weakening of a synaptic weight in the absence of synapse stimulation, and modulation of synapse with synchronous irritation of some other synaptic junction.
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##article.viewOnOriginalSite##About the authors
Maxim N Nazarov
National Research University of Electronic Technology
Email: Nazarov-Maximilian@yandex.ru
Assistant, Dept. of Higher Mathematics – 1. 5, Proezd 4806, Moscow, Zelenograd, 124498, Russia
References
- Голубев Ю. Ф. Нейронные сети в мехатронике // Фундамент. и прикл. Матем., 2005. Т. 11, № 8. С. 81–103.
- Wasserman P. D. Neural Computing, theory and practice. New York: Van Nostrand Reinhold, 1989.
- Kohonen T. Self-Organizing Maps. Third extended edition / Springer Series in Information Sciences. Vol. 30. Berlin: Springer-Verlag, 2001. xx+501 pp.
- Hodgkin A. L., Huxley A. F. A quantitative description of membrane current and its application to conduction and excitation in nerve // J. Physiol., 1952. no. 4. Pp. 500–544.
- Майоров В. В., Мышкин И. Ю. Математическое моделирование нейронной сети на основе уравнений с запаздыванием // Матем. моделирование, 1990. Т. 2, № 11. С. 64–76.
- Дунаева О. А. Принципы построения слоистых нейронных сетей на основе импульсных нейронов // Модел. и анализ информ. систем., 2011. Т. 18, № 2. С. 65–76.
- Коновалов Е. В. Задача адаптации обобщенного нейронного элемента // Модел. и анализ информ. систем., 2012. Т. 19, № 1. С. 69–83.
- Han J.-H., Kushner S. A., Yiu A. P., Cole C. J., Matynia A., Brown R. A., Neve R. A., Guzowski J. F., Silva A. J., Josselyn S. A. Neuronal Competition and Selection During Memory Formation // Science, 2007. Vol. 316, no. 5823. Pp. 457–460.
- Antonov I., Antonova I., Kandel E. R., Hawkinssend R. D. Activity-Dependent Presynaptic Facilitation and Hebbian LTP Are Both Required and Interact during Classical Conditioning in Aplysia // Neuron, 2003. Vol. 37, no. 1. Pp. 135–147.
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