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Article
Publication date: 19 June 2017

Qi Wang, Pengcheng Zhang, Jianming Wang, Qingliang Chen, Zhijie Lian, Xiuyan Li, Yukuan Sun, Xiaojie Duan, Ziqiang Cui, Benyuan Sun and Huaxiang Wang

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the…

Abstract

Purpose

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise.

Design/methodology/approach

This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity.

Findings

Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages.

Originality/value

EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

Details

Sensor Review, vol. 37 no. 3
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 1 September 2000

Ziyu Lin

An emerging, globally Web‐based Chinese language virtual library offers unprecedented content availability and user accessibility. Virtual and physical libraries are…

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Abstract

An emerging, globally Web‐based Chinese language virtual library offers unprecedented content availability and user accessibility. Virtual and physical libraries are defined, and compared, in terms of bibliographical searching. Then, the size of the Chinese language virtual library is estimated and its future development is predicted. The quantitative analysis concentrates on the content of this virtual library through examining the subject directories of more than 100 of its search engines. The findings show that 20 percent of the subject categories provide 80 percent of online access activities. Many subject categories characterise values of the Chinese‐speaking world. Discussion continues with structural and functional analyses of Chinese language search engines that support this virtual library. Further, an analytic overview is presented of Chinese language applications that render the necessary and sufficient computational linguistic conditions for utilising Chinese language online resources.

Details

Library Hi Tech, vol. 18 no. 3
Type: Research Article
ISSN: 0737-8831

Keywords

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