Remembering Key Features of Visual Images Based on Spike Timing Dependent Plasticity of Spiking Neurons

Qingxiang Wu, R. Cai, T. McGinnity, L. Maguire, J. Harkin
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引用次数: 4

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.
基于脉冲神经元时变可塑性的视觉图像关键特征记忆
大脑具有强大的记忆图像关键特征的能力。基于脉冲神经元与脉冲时间相关的可塑性原理和视觉系统中的on /OFF通路,提出了一种用于记忆视觉图像关键特征的脉冲神经网络。仿真结果表明,该网络能够根据基于脉冲时间依赖可塑性的学习规则记忆关键特征。网络的原理可以用来解释一个基于尖峰神经元的系统如何存储视觉图像的关键特征。此外,该网络还可以应用于基于峰值神经元的人工智能系统,以支持对视觉图像的处理。
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