Spiking Neural Network Performs Discrete Cosine Transform for Visual Images

被引：0

作者：

Wu, Qingxiang ^{[1
]}

McGinnity, T. M. ^{[1
]}

Maguire, Liam ^{[1
]}

Ghani, Arfan ^{[1
]}

Condell, Joan ^{[1
]}

机构：

[1] Univ Ulster, Intelligent Syst Res Ctr, Derry BT48 7JL, North Ireland

来源：

EMERGING INTELLIGENT COMPUTING TECHNOLOGY AND APPLICATIONS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE | 2009年 / 5755卷

关键词：

spiking neural networks; visual system; discrete cosine transform; visual image;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The human visual system demonstrates powerful image processing functionalities. Inspired by the principles from neuroscience, a spiking neural network is proposed to perform the discrete cosine transform for visual images. The structure and the properties of the network are detailed in this paper. Simulation results show that the network is able to perform the discrete cosine transform for visual images. Based on this mechanism, the key features can be extracted in ON/OFF neuron arrays. These key features can be used to reconstruct the visual images. The network can be used to explain how the spiking neuron-based system can perform key feature extraction. The differences between the discrete cosine transform and the spiking neural network transform are discussed.

引用

页码：21 / 29

页数：9

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