scholarly journals Unsupervised radar signal recognition based on multi‐block – Multi‐view Low‐Rank Sparse Subspace Clustering

2021 ◽  
Author(s):  
Lutao Liu ◽  
Shuai Xu
Keyword(s):  
Subspace Clustering ◽  
Low Rank ◽  
Radar Signal ◽  
Signal Recognition ◽  
Sparse Subspace Clustering

scholarly journals Multi-view low-rank sparse subspace clustering

2018 ◽  
Vol 73 ◽  
pp. 247-258 ◽  
Author(s):  
Maria Brbić ◽  
Ivica Kopriva
Keyword(s):  
Subspace Clustering ◽  
Low Rank ◽  
Sparse Subspace Clustering

scholarly journals Low-rank sparse subspace clustering with a clean dictionary

2021 ◽  
Vol 15 ◽  
pp. 174830262199962
Author(s):  
Cong-Zhe You ◽  
Zhen-Qiu Shu ◽  
Hong-Hui Fan
Keyword(s):  
Optimization Problem ◽  
Clustering Algorithms ◽  
Subspace Clustering ◽  
Low Rank ◽  
Data Matrix ◽  
Image Clustering ◽  
Convex Optimization Problem ◽  
Data Points ◽  
Low Rank Representation ◽  
Sparse Subspace Clustering

Low-Rank Representation (LRR) and Sparse Subspace Clustering (SSC) are considered as the hot topics of subspace clustering algorithms. SSC induces the sparsity through minimizing the l1-norm of the data matrix while LRR promotes a low-rank structure through minimizing the nuclear norm. In this paper, considering the problem of fitting a union of subspace to a collection of data points drawn from one more subspaces and corrupted by noise, we pose this problem as a non-convex optimization problem, where the goal is to decompose the corrupted data matrix as the sum of a clean and self-expressive dictionary plus a matrix of noise. We propose a new algorithm, named Low-Rank and Sparse Subspace Clustering with a Clean dictionary (LRS2C2), by combining SSC and LRR, as the representation is often both sparse and low-rank. The effectiveness of the proposed algorithm is demonstrated through experiments on motion segmentation and image clustering.

scholarly journals Sparse subspace clustering via Low-Rank structure propagation

2019 ◽  
Vol 95 ◽  
pp. 261-271 ◽  
Author(s):  
Yao Sui ◽  
Guanghui Wang ◽  
Li Zhang
Keyword(s):  
Subspace Clustering ◽  
Low Rank ◽  
Sparse Subspace Clustering

Graph constraint-based robust latent space low-rank and sparse subspace clustering

2019 ◽  
Vol 32 (12) ◽  
pp. 8187-8204
Author(s):  
Yunjun Xiao ◽  
Jia Wei ◽  
Jiabing Wang ◽  
Qianli Ma ◽  
Shandian Zhe ◽  
...  
Keyword(s):  
Subspace Clustering ◽  
Low Rank ◽  
Latent Space ◽  
Sparse Subspace Clustering

Sparse subspace clustering with low-rank transformation

2017 ◽  
Vol 31 (7) ◽  
pp. 3141-3154
Author(s):  
Gang Xu ◽  
Mei Yang ◽  
Qiufeng Wu
Keyword(s):  
Subspace Clustering ◽  
Low Rank ◽  
Rank Transformation ◽  
Sparse Subspace Clustering
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