Results 81 to 90 of about 27,220,972 (292)

KernelICA : Kernel Independent Component Analysis

, 2021
The kernel independent component analysis (kernel ICA) method introduced by Bach and Jordan (2003) .
Koesner, Christoph L., Nordhausen, Klaus
core   +1 more source

Reward processing in children with affective dysregulation

JCPP Advances, EarlyView.
Abstract Background Affective dysregulation (AD) in children is characterized by irritability, anger, and frequent intense temper outbursts. Considerable evidence implies altered processing of frustration about missed rewards, but few studies investigated the preceding and thus potentially predictive reward anticipation and initial delivery processing ...
Pascal‐M. Aggensteiner, Francisca Giller, Nathalie Holz, Anna Kaiser, Christine Igel, Sarah Hohmann, Manfred Döpfner, Veit Roessner, Christian Beste, Tobias Banaschewski, Daniel Brandeis, on behalf ofthe ADOPT Consortium   +11 more
wiley   +1 more source

FACE RECOGNITION USING PCA, LDA AND ICA APPROACHES ON COLORED IMAGES

Electrica, 2002
In this paper, the performances of appearance-based statistical methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Independent Component Analysis (ICA) are tested and compared for the recognition of colored face ...
Önsen TOYGAR, Adnan ACAN
doaj   +2 more sources

Measuring the accuracy of ICA-based artifact removal from TMS-evoked potentials

Brain Stimulation
Background: The analysis and interpretation of transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) relies on successful cleaning of the artifacts, which typically mask the early (0–30 ms) TEPs.
Iiris Atti, Paolo Belardinelli, Risto J. Ilmoniemi, Johanna Metsomaa   +3 more
doaj   +1 more source

Determining Number of Independent Sources in Undercomplete Mixture

EURASIP Journal on Advances in Signal Processing, 2009
Separation of independent sources using independent component analysis (ICA) requires prior knowledge of the number of independent sources. Performing ICA when the number of recordings is greater than the number of sources can give erroneous results.
Dinesh K. Kumar, Ganesh R. Naik
doaj   +1 more source

Improvement of Image Classification with Wavelet and Independent Component Analysis (ICA) based on a Structured Neural Network

, 2006
Image classification is a challenging problem in organizing a large image database. However, an effective method for such an objective is still under investigation.
Weibao Zou, Chi, Zheru, Li, Yan, Zheru Chi, Lo, King Chuen, King Chuen Lo, Yan Li, Zou, Weibao   +7 more
core   +1 more source

Non-negative mixtures [PDF]

, 2010
This is the author's accepted pre-print of the article, first published as M. D. Plumbley, A. Cichocki and R. Bro. Non-negative mixtures. In P. Comon and C. Jutten (Ed), Handbook of Blind Source Separation: Independent Component Analysis and Applications.
M. D. Plumbley, Bro, Rasmus, Plumbley, MD, Cichocki, A, Cichocki, A., Bro, R, Plumbley, M.D., A. Cichocki, R. Bro, M.D. Plumbley   +9 more
core   +1 more source

Identifiable regional and neural network abnormalities in early childhood anxiety

JCPP Advances, EarlyView.
Abstract Background Although the neural underpinnings of anxiety have been investigated, most research has been confined to adolescence and adulthood, with less of a focus on the early childhood period. Little is known about the role of anticipatory fear processing early childhood, which is a sensitive period for anxiety development.
Khalil I. Thompson, Yiwen Zhang, Denny Schaedig, Anna Bankston, Anoushka Parnerkar, Shrinidhi Jeyaram, Nadine Melhem, Susan B. Perlman   +7 more
wiley   +1 more source

Uncovering beam position monitor noise at the Relativistic Heavy Ion Collider

Physical Review Special Topics. Accelerators and Beams, 2015
We apply the independent component analysis (ICA) algorithm to uncover intrinsic noise in the beam position monitor (BPM) system. Numerical simulations found that ICA is efficient in the BPM noise estimation.
X. Shen, S. Y. Lee, M. Bai
doaj   +1 more source