Näytetään 1 - 8 yhteensä 8 tuloksesta haulle 'independent ((component analysis) OR (content analysis)) (ica)', hakuaika: 0,06s Tarkenna hakua
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    Independent component analysis (ICA) in analysing child high-density event-related potential (ERP) and current source density (CSD) data Tekijä Tanskanen, Annika

    Julkaistu 2008
    Aiheet: “…independent component analysis (ICA)…”
    Hae kokoteksti
    Pro gradu
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    Newton update based independent vector analysis with various source density models Tekijä Sipilä, Mika

    Julkaistu 2022
    “…Tutkielmassa käytetyt IVA algoritmit sekä niiden suorituskykyyn liittyvät indeksit ovat julkaistu R-paketissa ivaBSS osana tutkielmaa Blind source separation methods (BSS) are used to estimate latent source signals from their mixed observations when the mixing environment is unknown. Independent component analysis (ICA) is a BSS method, which aims to recover the sources by maximizing the independence between the estimated sources. …”
    Hae kokoteksti Hae kokoteksti
    Pro gradu
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    Exploring EEG recordings of Focused Attention Meditation with Fourier-ICA Tekijä Heinilä, Erkka

    Julkaistu 2017
    “…This study uses a variant of Independent Component Analysis (ICA) called Fourier-ICA to analyze EEG data from meditation sessions and shows that ICA can be used to do much more than just remove artifacts, which is the normal use case in EEG studies. …”
    Hae kokoteksti Hae kokoteksti
    Pro gradu
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    Korkeaintensiteettisen intervalliharjoituksen akuutit vaikutukset aivojen lepoaktiivisuuteen 16-17-vuotiailla nuorilla : MEG-tutkimus Tekijä Kullberg, Tiina

    Julkaistu 2020
    “…Additionally, group level Fourier ICA (independent component analysis) was experimentally applied to examine spatial differences of peak frequency changes more in detail. …”
    Hae kokoteksti Hae kokoteksti
    Pro gradu
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    Decoding four-finger proprioceptive and tactile stimuli from magnetoencephalography Tekijä Nyländen, Paavo

    Julkaistu 2024
    “…Preprocessing steps included noise reduction techniques such as oversampled temporal projection (OTP), temporal signal space separation (tSSS), and independent component analysis (ICA). Features for decoding were extracted from the temporal changes in MEG signals using a sliding time window analysis, and SVMs were employed for classification. …”
    Hae kokoteksti Hae kokoteksti
    Pro gradu
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