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Proceedings Paper

Modular tensor sparsity preserving projection algorithm for dimension reduction
Author(s): Mohan Zhang; Mingming Qi; Peng Wang; Dongdong Lv
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Paper Abstract

This paper proposes a modular tensor sparsity preserving projection (MTSPP) algorithm. This algorithm uniformly partitions the high-dimensional matrix data and builds third order tensor data, determines the weight of sparse reconstruction of all samples and applies it to the sparsity preserving projection of the third order tensor. Experiments finally indicate that MTSPP improves the robust performance of the global sparse representation-based dimension reduction algorithm by weighted sparse representation and spatial relationship of characteristics within the module and between modules.

Paper Details

Date Published: 3 December 2015
PDF: 5 pages
Proc. SPIE 9794, Sixth International Conference on Electronics and Information Engineering, 97942K (3 December 2015); doi: 10.1117/12.2203470
Show Author Affiliations
Mohan Zhang, Tongji Univ. (China)
Mingming Qi, Shaoxing Univ. (China)
Peng Wang, Fudan Univ. (China)
Shanghai Cloud Valley Development Co., Ltd. (China)
Dongdong Lv, Tongji Univ. (China)

Published in SPIE Proceedings Vol. 9794:
Sixth International Conference on Electronics and Information Engineering
Qiang Zhang, Editor(s)

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