Results 181 to 190 of about 5,105 (201)
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Neonatal seizure localization using PARAFAC decomposition
Clinical Neurophysiology, 2009The description and evaluation of two EEG-based algorithms for automatic and objective determination of the seizure location in the neonatal brain as it is reflected on the scalp.Each algorithm extracts the electrical potential distribution of the seizure over the scalp using the higher-order canonical decomposition or Parallel Factor Analysis (PARAFAC)
Deburchgraeve, W +7 more
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Modeling Food Fluorescence with PARAFAC
2018Parallel factor analysis (PARAFAC) of food fluorescence has found many applications in food science, such as in non-contact and non-destructive food characterization, the detection of food adulteration, and the authentication of geographical and botanical origins of food products. This Chapter presents a theoretical background of the PARAFAC method and
Ackovic, Lea Lenhardt +4 more
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Blind PARAFAC receivers for DS-CDMA systems
IEEE Transactions on Signal Processing, 2000This paper links the direct-sequence code-division multiple access (DS-CDMA) multiuser separation-equalization-detection problem to the parallel factor (PARAFAC) model, which is an analysis tool rooted in psychometrics and chemometrics. Exploiting this link, it derives a deterministic blind PARAFAC DS-CDMA receiver with performance close to non-blind ...
Nicholas D. Sidiropoulos +2 more
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Deflation method for CANDECOMP/PARAFAC tensor decomposition
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014CANDECOMP/PARAFAC tensor decomposition (CPD) approximates multiway data by rank-1 tensors. Unlike matrix decomposition, the procedure which estimates the best rank-R tensor approximation through R sequential best rank-1 approximations does not work for tensors, because the deflation does not always reduce the tensor rank.
Anh Huy Phan 0001 +2 more
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Advances in PARAFAC Using Parallel Block Decomposition
2009Parallel factor analysis (PARAFAC) is a multi-way decomposition method which allows to find hidden factors from the raw tensor data with many potential applications in neuroscience, bioinformatics, chemometrics etc [1,2]. The Alternating Least Squares (ALS) algorithm can explain the raw tensor by a small number of rank-one tensors with a high fitness ...
Anh Huy Phan 0001, Andrzej Cichocki
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Fluorescence spectroscopy and PARAFAC in the analysis of yogurt
Chemometrics and Intelligent Laboratory Systems, 2005Abstract Parallel factor (PARAFAC) analysis and fluorescence spectroscopy were applied in the evaluation of yogurt during storage. Fluorescence landscapes with excitation wavelengths from 270 to 550 nm and emission wavelengths in the range 310–590 nm were obtained from front-face fluorescence measurements directly on yogurt samples during two storage
Christensen, J. +2 more
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Improving PARAFAC-ALS performance by initialization
2018The CANDECOMP/PARAFAC (CP) model (Carroll and Chang, 1970; Harshman, 1970) is a trilinear decomposition which provides a low rank approximation of a three-way array in a manner that preserves the multi-mode structure of the data. This is achieved by estimating three sets of parameters, one for each dimension of the array, namely observation units ...
Simonacci V, Gallo M
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