A spatial domain sigma-delta modulator using discrete-time cellular neural networks

被引：0

作者：

Aomori, Hisashi ^{[1
]}

Otake, Tsuyoshi ^{[2
]}

Takahashi, Nobuaki ^{[3
]}

Tanaka, Mamoru ^{[1
]}

机构：

[1] Sophia Univ, Dept Elect & Elect Engn, Chiyoda Ku, 7-1 Kioi Cho, Tokyo 1028554, Japan

[2] Univ Tamagawa, Dept Media Network Sci, Tokyo 1948610, Japan

[3] IBM Japan Ltd, IBM Engn & Technol Serv, Kanagawa 2428502, Japan

来源：

PROCEEDINGS OF THE 2006 10TH IEEE INTERNATIONAL WORKSHOP ON CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS | 2006年

关键词：

image reconstruction; image binarization; C-template; DT-CNN;

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：

In this paper, a novel spatial domain sigma-delta modulator using discrete-time cellular neural networks (DT-CNNs) is proposed. Since the nature of CNN dynamics with the output function which has two saturation regions is to binarize the input image, CNNs have a capabilities as a spatial domain sigma-delta modulator. In the proposed architecture, the A-template is used for a digital to analogue converter (DAC), the C-template works as an integrator, and the nonlinear output function is for the bilevel output Moreover, the dynamics is designed for obtaining an optimal reconstruction image. The experimental results show a good reconstruction performance and capabilities of CNN as a sigma-delta modulator.

引用

页码：251 / +

页数：2

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