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Browsing by Author "Theis, F.J."

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  • Denoising using local projective subspace methods
    Publication . Gruber, P.; Stadlthanner, K.; Böhm, M.; Theis, F.J.; Lang, E.W.; Tomé, A.M.; Teixeira, Ana; Puntonet, C.G.; Gorriz Saéz, J.M.
    In this paper we present denoising algorithms for enhancing noisy signals based on Local ICA (LICA), Delayed AMUSE (dAMUSE) and Kernel PCA (KPCA). The algorithm LICA relies on applying ICA locally to clusters of signals embedded in a high-dimensional feature space of delayed coordinates. The components resembling the signals can be detected by various criteria like estimators of kurtosis or the variance of autocorrelations depending on the statistical nature of the signal. The algorithm proposed can be applied favorably to the problem of denoising multi-dimensional data. Another projective subspace denoising method using delayed coordinates has been proposed recently with the algorithm dAMUSE. It combines the solution of blind source separation problems with denoising efforts in an elegant way and proofs to be very efficient and fast. Finally, KPCA represents a non-linear projective subspace method that is well suited for denoising also. Besides illustrative applications to toy examples and images, we provide an application of all algorithms considered to the analysis of protein NMR spectra.
    2006Journal article Open access Show more
  • On the use of simulated annealing to automatically assign decorrelated components in second-order blind source separation
    Publication . Bohm, M.; Stadlthanner, K.; Gruber, P.; Theis, F.J.; Lang, E.W.; Tome, A.M.; Teixeira, Ana; Gronwald, W.; Kalbitzer, H.R.
    —In this paper, an automatic assignment tool, called BSS-AutoAssign, for artifact-related decorrelated components within a second-order blind source separation (BSS) is presented. The latter is based on the recently proposed algorithm dAMUSE, which provides an elegant solution to both the BSS and the denoising problem simultaneously. BSS-AutoAssign uses a local principal component analysis (PCA)to approximate the artifact signal and defines a suitable cost function which is optimized using simulated annealing. The algorithms dAMUSE plus BSS-AutoAssign are illustrated by applying them to the separation of water artifacts from two-dimensional nuclear overhauser enhancement (2-D NOESY) spectroscopy signals of proteins dissolved in water.
    2006Journal article Open access Show more