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Автор C C Alan Fung
Автор K Y Michael Wong
Автор Si Wu
Дата выпуска 2009-12-01
dc.description We introduce an analytically solvable model of two-dimensional continuous attractor neural networks (CANNs). The synaptic input and the neuronal response form Gaussian bumps in the absence of external stimuli, and enable the network to track external stimuli by its translational displacement in the two-dimensional space. Basis functions of the two-dimensional quantum harmonic oscillator in polar coordinates are introduced to describe the distortion modes of the Gaussian bump. The perturbative method is applied to analyze its dynamics. Testing the method by considering the network behavior when the external stimulus abruptly changes its position, we obtain results of the reaction time and the amplitudes of various distortion modes, with excellent agreement with simulation results.
Формат application.pdf
Издатель Institute of Physics Publishing
Копирайт © 2009 IOP Publishing Ltd
Название Tracking dynamics of two-dimensional continuous attractor neural networks
Тип paper
DOI 10.1088/1742-6596/197/1/012017
Electronic ISSN 1742-6596
Print ISSN 1742-6588
Журнал Journal of Physics: Conference Series
Том 197
Первая страница 12017
Последняя страница 12026
Выпуск 1

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