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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

7. Generalized Principal Component Analysis

verfasst von : Xiangyu Kong, Changhua Hu, Zhansheng Duan

Erschienen in: Principal Component Analysis Networks and Algorithms

Verlag: Springer Singapore

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Abstract

Recently, as a powerful feature extraction technique, generalized eigen decomposition (GED) has been attracting great attention and been widely used in many fields, e.g., spectral estimation (Huanqun et al. IEEE Trans Acoust Speech Signal Process 34(2), 272–284, 1986), blind source separation (Chang et al. IEEE Trans Acoust Speech Signal Process 48(3), 900–907, 2000), digital mobile communications (Comon and Golub Proc IEEE 78(8), 1327–1343, 1990), and antenna array processing (Choi et al. IEEE Trans Veh Technol 51(5), 808–816, 2002; Morgan IEEE Trans Commun 51(3), 476–488, 2003).

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Vorheriges Kapitel Deterministic Discrete-Time System for the Analysis of Iterative Algorithms
Nächstes Kapitel Coupled Principal Component Analysis
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Metadaten
Titel
Generalized Principal Component Analysis
verfasst von
Xiangyu Kong
Changhua Hu
Zhansheng Duan
Copyright-Jahr
2017
Verlag
Springer Singapore
Buch
Principal Component Analysis Networks and Algorithms

Print ISBN: 978-981-10-2913-4

Electronic ISBN: 978-981-10-2915-8

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-981-10-2915-8_7