@article{ZieheMuellerNolteetal.2000,
  author    = {Ziehe, Andreas and M{\"u}ller, Klaus-Robert and Nolte, G. and Mackert, B.-M. and Curio, Gabriel},
  title     = {Artifact reduction in magnetoneurography based on time-delayed second-order correlations},
  year      = {2000},
  language  = {en}
}
@article{ZieheLaskovNolteetal.2004,
  author    = {Ziehe, Andreas and Laskov, Pavel and Nolte, G and M{\"u}ller, Klaus-Robert},
  title     = {A fast algorithm for joint diagonalization with non-orthogonal transformations and its application to blind source separation},
  year      = {2004},
  abstract  = {A new efficient algorithm is presented for joint diagonalization of several matrices. The algorithm is based on the Frobenius-norm formulation of the joint diagonalization problem, and addresses diagonalization with a general, non- orthogonal transformation. The iterative scheme of the algorithm is based on a multiplicative update which ensures the invertibility of the diagonalizer. The algorithm's efficiency stems from the special approximation of the cost function resulting in a sparse, block-diagonal Hessian to be used in the computation of the quasi-Newton update step. Extensive numerical simulations illustrate the performance of the algorithm and provide a comparison to other leading diagonalization methods. The results of such comparison demonstrate that the proposed algorithm is a viable alternative to existing state-of-the-art joint diagonalization algorithms. The practical use of our algorithm is shown for blind source separation problems},
  language  = {en}
}
@article{WuebbelerZieheMackertetal.2000,
  author    = {W{\"u}bbeler, G. and Ziehe, Andreas and Mackert, B.-M. and M{\"u}ller, Klaus-Robert and Trahms, L. and Curio, Gabriel},
  title     = {Independent component analysis of noninvasively recorded cortical magnetic DC-fields in humans},
  year      = {2000},
  language  = {en}
}
@article{ParraSpenceSajdaetal.2000,
  author    = {Parra, L. and Spence, C. and Sajda, P. and Ziehe, Andreas and M{\"u}ller, Klaus-Robert},
  title     = {Unmixing hyperspectral data},
  year      = {2000},
  language  = {en}
}
@article{NolteMeineckeZieheetal.2006,
  author    = {Nolte, Guido and Meinecke, Frank C. and Ziehe, Andreas and M{\"u}ller, Klaus-Robert},
  title     = {Identifying interactions in mixed and noisy complex systems},
  doi       = {10.1103/Physreve.73.051913},
  year      = {2006},
  abstract  = {We present a technique that identifies truly interacting subsystems of a complex system from multichannel data if the recordings are an unknown linear and instantaneous mixture of the true sources. The method is valid for arbitrary noise structure. For this, a blind source separation technique is proposed that diagonalizes antisymmetrized cross- correlation or cross-spectral matrices. The resulting decomposition finds truly interacting subsystems blindly and suppresses any spurious interaction stemming from the mixture. The usefulness of this interacting source analysis is demonstrated in simulations and for real electroencephalography data},
  language  = {en}
}
@article{MuellerVigarioMeineckeetal.2004,
  author    = {M{\"u}ller, Klaus-Robert and Vigario, R. and Meinecke, Frank C. and Ziehe, Andreas},
  title     = {Blind source separation techniques for decomposing event-related brain signals},
  issn      = {0218-1274},
  year      = {2004},
  abstract  = {Recently blind source separation (BSS) methods have been highly successful when applied to biomedical data. This paper reviews the concept of BSS and demonstrates its usefulness in the context of event-related MEG measurements. In a first experiment we apply BSS to artifact identification of raw MEG data and discuss how the quality of the resulting independent component projections can be evaluated. The second part of our study considers averaged data of event-related magnetic fields. Here, it is particularly important to monitor and thus avoid possible overfitting due to limited sample size. A stability assessment of the BSS decomposition allows to solve this task and an additional grouping of the BSS components reveals interesting structure, that could ultimately be used for gaining a better physiological modeling of the data},
  language  = {en}
}
@article{MeineckeZieheKurthsetal.2005,
  author    = {Meinecke, Frank C. and Ziehe, Andreas and Kurths, J{\"u}rgen and M{\"u}ller, Klaus-Robert},
  title     = {Measuring phase synchronization of superimposed signals},
  issn      = {0031-9007},
  year      = {2005},
  abstract  = {Phase synchronization is an important phenomenon that occurs in a wide variety of complex oscillatory processes. Measuring phase synchronization can therefore help to gain fundamental insight into nature. In this Letter we point out that synchronization analysis techniques can detect spurious synchronization, if they are fed with a superposition of signals such as in electroencephalography or magnetoencephalography data. We show how techniques from blind source separation can help to nevertheless measure the true synchronization and avoid such pitfalls},
  language  = {en}
}