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ICASSP
2008
IEEE

Robust correlation analysis with an application to functional MRI

11 years 6 months ago
Robust correlation analysis with an application to functional MRI
Correlation is often used to measure the similarity between signals and is an important tool in signal and image processing. In some applications it is common that signals are corrupted by local bursts of noise. This adversely affects the performance of signal recognition algorithms. This paper presents a novel correlation estimator, which is robust to locally corrupted signals. The estimator is generalized to multivariate correlation analysis (general linear model, GLM, and canonical correlation analysis, CCA). Synthetic functional MRI data is used to demonstrate the estimator, and its robustness is shown to increase the performance of signal detection.
Joakim Rydell, Magnus Borga, Hans Knutsson
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICASSP
Authors Joakim Rydell, Magnus Borga, Hans Knutsson
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