Redundant 发表于 2025-3-23 11:30:47

Reproduction of Paramyxoviruses,a significant role in the big-data era, when large datasets are often outlier corrupted. In this chapter, we present the theoretical foundations of L1-PCA, optimal and state-of-the-art approximate algorithms for its implementation, and some numerical studies that demonstrate its favorable performanc

Abjure 发表于 2025-3-23 15:09:46

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种子 发表于 2025-3-23 18:59:38

Damage and Fault Detection of Structures Using Principal Component Analysis and Hypothesis Testing,the intractable problem of Israel. No satisfactory Middle East policy will be possible for the West until the problem of Israel’s future is permanently settled; but even then the extremely difficult problem of achieving satisfactory relations with Arab nationalism will still have to be dealt with.

multiply 发表于 2025-3-23 23:06:39

PCA, Kernel PCA and Dimensionality Reduction in Hyperspectral Images,ne hand, iron-stone deposits and, on the other hand, fast-flowing streams which were required from the fifteenth century onwards to operate bellows and forge-hammers used in the process of production.

DEMN 发表于 2025-3-24 02:53:25

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antedate 发表于 2025-3-24 08:56:30

Principal Component Analysis Techniques for Visualization of Volumetric Data,Overview:

osteocytes 发表于 2025-3-24 10:45:40

Application and Extension of PCA Concepts to Blind Unmixing of Hyperspectral Data with Intra-class Overview:

羊齿 发表于 2025-3-24 16:57:01

https://doi.org/10.1007/978-1-4613-3009-7rther helps overcome the model inconsistency and improve interpretability when applied to high-dimensional data. Model formulations and solution strategies of ePCA and sparse ePCA are discussed with real-world applications.

mutineer 发表于 2025-3-24 22:21:01

Book 2018lems related to dimensional reduction techniques and their extensions in detail. Bringing together research results previously scattered throughout many scientific journals papers worldwide, the book presents them in a methodologically unified form. Offering vital insights into the subject matter in

Musculoskeletal 发表于 2025-3-24 23:11:13

ied form. Offering vital insights into the subject matter in self-contained chapters that balance the theory and concrete applications, and especially focusing on open problems, it is essential reading for all researchers and practitioners with an interest in PCA.. . .978-981-13-4934-8978-981-10-6704-4
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查看完整版本: Titlebook: Advances in Principal Component Analysis; Research and Develop Ganesh R. Naik Book 2018 Springer Nature Singapore Pte Ltd. 2018 Principal C