Results 141 to 150 of about 1,503 (160)

Stability of CANDECOMP-PARAFAC tensor decomposition

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011
In this paper, stability of the CANDECOMP-PARAFAC (CP) tensor decomposition is addressed. It is done by deriving the Cramer-Rao lower bound (CRLB) on variance of an unbiased estimate of the tensor parameters, i.e. elements of its factor matrices, from its noisy observation (the tensor plus a random Gaussian i.i.d. tensor).
Petr Tichavsky, Zbynek Koldovsky
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Partial uniqueness in CANDECOMP/PARAFAC

Journal of Chemometrics, 2004
AbstractA key property of CANDECOMP/PARAFAC is the essential uniqueness it displays under certain conditions. It has been known for a long time that, when these conditions are not met, partial uniqueness may remain. Whereas considerable progress has been made in the study of conditions for uniqueness, the study of partial uniqueness has lagged behind ...
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Improving PARAFAC-ALS performance by initialization

2018
The 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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Multidimensional Noise Removal Method Based on PARAFAC Decomposition

2008
Multicomponent sensors are more and more developed since they allow to measure simultaneously several parameters. Thus, new kind of processing have been developed for some years. In this paper, we are particularly concerned with tensor signal processing for noise removal in multidimensional images.
Joyeux, Florian, Letexier, Damien, Bourennane, Salah, Blanc-Talon, Jacques   +3 more
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Blind PARAFAC receivers for DS-CDMA systems

IEEE Transactions on Signal Processing, 2000
This 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 ...
Sidiropoulos, N. D., Giannakis, G. B., Bro, R.   +2 more
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CANDECOMP/PARAFAC (CP) direction finding with multi-scale array

2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2013
In this paper, we introduce a novel direction of arrival (DOA) estimation algorithm for an array presenting multiple scales of invariance, based on a CANDECOMP/PARAFAC (CP) model of the data. The proposed approach is a generalization of the results given in [Sidiropoulos et al.'00] to an array presenting an arbitrary number of spatial invariances.
Miron, Sebastian, Yang, Song, Brie, David, Wong, Kainam   +3 more
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Deflation method for CANDECOMP/PARAFAC tensor decomposition

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014
CANDECOMP/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, Petr Tichavsky, Andrzej Cichocki   +2 more
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PARAFAC: An “Explanatory” Factor Analysis Procedure

The Journal of the Acoustical Society of America, 1971
Simple structure and other common principles of factor rotation do not in general provide strong grounds for attributing explanatory significance to the factors which they select. In contrast, it is shown that an extension of Cattell's principle of rotation to proportional profiles (PP) offers a basis for determining explanatory factors for three-way ...
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Improved PARAFAC Based Blind MIMO System Estimation

Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005., 2006
We consider the problem of frequency domain identification of a multiple-input multiple-output (MIMO) system driven by white, mutually independent unobservable inputs. In particular, we improve upon a method recently proposed by the authors [1] that uses PARAFAC decomposition of a tensor that is formed based on higher-order statistics of the system ...
null Yuanning Yu, A.P. Petropulu
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Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data

IEEE Transactions on Cybernetics, 2015
In recent years, low-rank tensor completion (LRTC) problems have received a significant amount of attention in computer vision, data mining, and signal processing. The existing trace norm minimization algorithms for iteratively solving LRTC problems involve multiple singular value decompositions of very large matrices at each iteration. Therefore, they
Yuanyuan, Liu, Fanhua, Shang, Licheng, Jiao, James, Cheng, Hong, Cheng   +4 more
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