Zobrazeno 1 - 10 of 47 pro vyhledávání: '"Maria, Sandsten"'
1
Akademický článek
Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairment
Autor: Oskar Keding, Emina Alickovic, Martin A. Skoglund, Maria Sandsten
Publikováno v: Frontiers in Neuroscience, Vol 18 (2024)
In the literature, auditory attention is explored through neural speech tracking, primarily entailing modeling and analyzing electroencephalography (EEG) responses to natural speech via linear filtering. Our study takes a novel approach, introducing
Externí odkaz: https://doaj.org/article/9e30c4a6533b466d87200bb3397e4577
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2
Akademický článek
Time-frequency feature extraction for classification of episodic memory
Autor: Rachele Anderson, Maria Sandsten
Publikováno v: EURASIP Journal on Advances in Signal Processing, Vol 2020, Iss 1, Pp 1-18 (2020)
Abstract This paper investigates the extraction of time-frequency (TF) features for classification of electroencephalography (EEG) signals and episodic memory. We propose a model based on the definition of locally stationary processes (LSPs), estimat
Externí odkaz: https://doaj.org/article/f26bdb30817c45a1a6210e32745ce54e
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3
Scaled reassigned spectrograms applied to linear transducer signals
Autor: Josefin, Starkhammar, Isabella, Reinhold, Tobias, Erlöv, Maria, Sandsten
Publikováno v: JASA express letters. 1(5)
This study evaluates the applicability of scaled reassigned spectrograms (ReSTS) on ultrasound radio frequency data obtained with a clinical linear array ultrasound transducer. The ReSTS's ability to resolve axially closely spaced objects in a phanto
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::d2d09bc9620e7c3989845e8e37a505c6
https://pubmed.ncbi.nlm.nih.gov/36154114
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10
Inference for time-varying signals using locally stationary processes
Autor: Rachele Anderson, Maria Sandsten
Publikováno v: Journal of Computational and Applied Mathematics. 347:24-35
Locally Stationary Processes (LSPs) in Silverman’s sense, defined by the modulation in time of a stationary covariance function, are valuable in stochastic modelling of time-varying signals. However, for practical applications, methods to conduct r
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::44c9418c1aa89c0c6125c3bc286edaa2
https://doi.org/10.1016/j.cam.2018.07.046
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