#### Filter Results:

#### Publication Year

1989

2016

#### Publication Type

#### Co-author

#### Key Phrase

#### Publication Venue

#### Data Set Used

Learn More

We review the development and extensions of the classical total least squares method and describe algorithms for its generalization to weighted and structured approximation problems. In the generic case, the classical total least squares problem has a unique solution, which is given in analytic form in terms of the singular value decomposition of the data… (More)

The electroencephalogram (EEG) is often contaminated by muscle artifacts. In this paper, a new method for muscle artifact removal in EEG is presented, based on canonical correlation analysis (CCA) as a blind source separation (BSS) technique. This method is demonstrated on a synthetic data set. The method outperformed a low-pass filter with different cutoff… (More)

- Dirk Timmerman, Lieveke Ameye, Daniela Fischerova, Elisabeth Epstein, Gian Benedetto Melis, Stefano Guerriero +10 others
- BMJ (Clinical research ed.)
- 2010

OBJECTIVES
To prospectively assess the diagnostic performance of simple ultrasound rules to predict benignity/malignancy in an adnexal mass and to test the performance of the risk of malignancy index, two logistic regression models, and subjective assessment of ultrasonic findings by an experienced ultrasound examiner in adnexal masses for which the simple… (More)

The main purpose of this special issue is to present an overview of the progress of a modeling technique which is known as total least squares (TLS) in computational mathematics and engineering, and as errors-in-variables (EIV) modeling or orthogonal regression in the statistical community. The TLS method is one of several linear parameter estimation… (More)

The Total Least Squares (TLS) method is a generalization of the least squares (LS) method for solving overdetermined sets of linear equations Ax b. The TLS method minimizes jjEj?r]jj F where r = b?(A+E)x, so that (b?r) 2 Range(A+E), given A 2 C mn , with m n and b 2 C m1. The most common TLS algorithm is based on the singular value decomposition (SVD) of A… (More)

1 This report is available by anonymous ftp from ftp.esat.kuleuven.ac.be in the directory pub/SISTA/lemmerli/reports/int9889.ps.Z. Abstract In this paper we develop a fast algorithm for the basic deconvolution problem. First we show that the kernel problem to be solved in the basic de-convolution problem is a so-called structured Total Least Squares… (More)

- Hans Hallez, Bart Vanrumste, Roberta Grech, Joseph Muscat, Wim De Clercq, Anneleen Vergult +5 others
- Journal of neuroengineering and rehabilitation
- 2007

BACKGROUND
The aim of electroencephalogram (EEG) source localization is to find the brain areas responsible for EEG waves of interest. It consists of solving forward and inverse problems. The forward problem is solved by starting from a given electrical source and calculating the potentials at the electrodes. These evaluations are necessary to solve the… (More)

- Ivana Despotovic, Perumpillichira J Cherian, Maarten De Vos, Hans Hallez, Wouter Deburchgraeve, Paul Govaert +6 others
- Human brain mapping
- 2013

Even though it is known that neonatal seizures are associated with acute brain lesions, the relationship of electroencephalographic (EEG) seizures to acute perinatal brain lesions visible on magnetic resonance imaging (MRI) has not been objectively studied. EEG source localization is successfully used for this purpose in adults, but it has not been… (More)

In biomedical signal processing, it is often the case that many sources are mixed into the measured signal. The goal is usually to analyze one or several of them separately. In the case of multichannel measurements, several blind source separation techniques are available for decomposing the signal into its components [e.g., independent component analysis… (More)