Abstract: Principal Component Analysis (PCA) aims to acquire the principal component space containing the essential structure of data, instead of being used for mining and extracting the essential ...
Inside living cells, mitochondria divide, lysosomes travel, and synaptic vesicles pulse—all in three dimensions (3Ds) and constant motion. Capturing these events with clarity is vital not just for ...
Abstract: Robust tensor principal component analysis (RTPCA) based on tensor singular value decomposition (t-SVD) separates the low-rank component and the sparse component from the multiway data. For ...
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