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3 December 2015 Modular tensor sparsity preserving projection algorithm for dimension reduction
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Proceedings Volume 9794, Sixth International Conference on Electronics and Information Engineering; 97942K (2015) https://doi.org/10.1117/12.2203470
Event: Sixth International Conference on Electronics and Information Engineering, 2015, Dalian, China
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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mohan Zhang, Mingming Qi, Peng Wang, and Dongdong Lv "Modular tensor sparsity preserving projection algorithm for dimension reduction", Proc. SPIE 9794, Sixth International Conference on Electronics and Information Engineering, 97942K (3 December 2015); https://doi.org/10.1117/12.2203470
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