Blind Source Separation Using Temporal Correlation, Non-Gaussianity and Conditional Heteroscedasticity

Independent component analysis separates latent sources from a linear mixture by assuming sources are statistically independent. In real world applications, hidden sources are usually non-Gaussian and have dependence among samples. In such case, both attributes should be considered jointly to obtain...
Ausführliche Beschreibung

Gespeichert in:
Autor*in:

Seyyed Hamed Fouladi [verfasserIn]

Ilangko Balasingham [verfasserIn]

Kimmo Kansanen [verfasserIn]

Tor Audun Ramstad [verfasserIn]

Format:

E-Artikel

Sprache:

Englisch

Erschienen:

2018

Schlagwörter:

Blind source separation

independent component analysis

autoregressive conditional heteroscedasticity

maximum likelihood

Fisher’s information matrix

Übergeordnetes Werk:

In: IEEE Access - IEEE, 2014, 6(2018), Seite 25336-25350

Übergeordnetes Werk:

volume:6 ; year:2018 ; pages:25336-25350

Links:

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Journal toc

DOI / URN:

10.1109/ACCESS.2018.2823381

Katalog-ID:

DOAJ053861175

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