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Block-mode discriminant analysis and its application to face and antenna signal recognition

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Abstract

In this paper we present a multi-linear algebra based approach for feature extraction and signal recognition. We call this method Block-Mode Discriminant Analysis (BMDA). Experimentations are carried out on the CMU-PIE benchmark database for the task of face recognition, and we further utilized our method for the application of the signal recognition of underground UWB dielectric resonator antennas. Experiments show that our proposed BMDA is more effective and fast than its predecessors.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant No. 51104157), the Ph.D. Programs Foundation of Ministry of Education of China (Grant No. 20110095120008), the China Postdoctoral Science Foundation (Grant No.20100481181), the Fundamental Research Funds for the Central Universities (Grant No. 2011QNA30), and Jiangsu Overseas Research & Training Program for University Prominent Young & Middle-aged Teachers and Presidents.

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Authors and Affiliations

  1. College of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China

    Chen Wei & Gao Jing

  2. State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing, 100083, China

    Tian Zijian, Chen Wenchao & Zhiyong Liu

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  1. Chen Wei
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  2. Gao Jing
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  3. Tian Zijian
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  4. Chen Wenchao
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  5. Zhiyong Liu
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Correspondence to Chen Wei.

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Wei, C., Jing, G., Zijian, T. et al. Block-mode discriminant analysis and its application to face and antenna signal recognition. Multimed Tools Appl 71, 1599–1613 (2014). https://doi.org/10.1007/s11042-012-1295-6

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