DocumentCode
2152133
Title
Remembering Key Features of Visual Images Based on Spike Timing Dependent Plasticity of Spiking Neurons
Author
Wu, QingXiang ; Cai, Rongtai ; McGinnity, T.M. ; Maguire, Liam ; Harkin, Jim
Author_Institution
Sch. of Phys. & Optoelectron. Technol., Fujian Normal Univ., Fuzhou, China
fYear
2009
fDate
17-19 Oct. 2009
Firstpage
1
Lastpage
5
Abstract
The brain has the powerful capability of remembering key features of images. Based on the principle of spike timing dependent plasticity of spiking neurons and the ON/OFF pathways in the visual system, a spiking neural network is proposed to remember key features of visual images. The simulation results show that the network is capable of remembering key features according to a learning rule based on spike timing dependent plasticity. The principle of the network can be used to explain how a spiking neuron-based system can store the key features of visual images. Furthermore, the network can be applied to spiking neuron based artificial intelligent systems to support the processing visual images.
Keywords
artificial intelligence; brain; neural nets; neurophysiology; visual perception; artificial intelligent systems; learning rule; spike timing dependent plasticity; spiking neural network; spiking neurons; visual images; Artificial intelligence; Biological neural networks; Brain modeling; Equations; Humans; Intelligent systems; Neurons; Retina; Timing; Visual system;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location
Tianjin
Print_ISBN
978-1-4244-4129-7
Electronic_ISBN
978-1-4244-4131-0
Type
conf
DOI
10.1109/CISP.2009.5303978
Filename
5303978
Link To Document