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Seydlitz Erdkunde 2
(1996)
Usually, noise is considered to be destructive. We present a new method that constructively injects noise to assess the reliability and the grouping structure of empirical ICA component estimates. Our method can be viewed as a Monte-Carlo-style approximation of the curvature of some performance measure at the solution. Simulations show that the true root-mean-squared angle distances between the real sources and the source estimates can be approximated well by our method. In a toy experiment, we see that we are also able to reveal the underlying grouping structure of the extracted ICA components. Furthermore, an experiment with fetal ECG data demonstrates that our approach is useful for exploratory data analysis of real-world data. (C) 2003 Elsevier B.V. All rights reserved
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
The Cassini-Huygens Cosmic Dust Analyzer (CDA) is intended to provide direct observations of dust grains with masses between 10(-19) and 10(-9) kg in interplanetary space and in the jovian and saturnian systems, to investigate their physical, chemical and dynamical properties as functions of the distances to the Sun, to Jupiter and to Saturn and its satellites and rings, to study their interaction with the saturnian rings, satellites and magnetosphere. Chemical composition of interplanetary meteoroids will be compared with asteroidal and cometary dust, as well as with Saturn dust, ejecta from rings and satellites. Ring and satellites phenomena which might be effects of meteoroid impacts will be compared with the interplanetary dust environment. Electrical charges of particulate matter in the magnetosphere and its consequences will be studied, e.g. the effects of the ambient plasma and the magnetic held on the trajectories of dust particles as well as fragmentation of particles due to electrostatic disruption. The investigation will be performed with an instrument that measures the mass, composition, electric charge, speed, and flight direction of individual dust particles. It is a highly reliable and versatile instrument with a mass sensitivity 106 times higher than that of the Pioneer 10 and I I dust detectors which measured dust in the saturnian system. The Cosmic Dust Analyzer has significant inheritance from former space instrumentation developed for the VEGA, Giotto, Galileo, and Ulysses missions. It will reliably measure impacts from as low as I impact per month up to 104 impacts per second. The instrument weighs 17 kg and consumes 12 W, the integrated time-of-flight mass spectrometer has a mass resolution of up to 50. The nominal data transmission rate is 524 bits/s and varies between 50 and 4192 bps
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
This paper proposes a new independent component analysis (ICA) method which is able to unmix overcomplete mixtures of sparce or structured signals like speech, music or images. Furthermore, the method is designed to be robust against outliers, which is a favorable feature for ICA algorithms since most of them are extremely sensitive to outliers. Our approach is based on a simple outlier index. However, instead of robustifying an existing algorithm by some outlier rejection technique we show how this index can be used directly to solve the ICA problem for super-Gaussian sources. The resulting inlier-based ICA (IBICA) is outlier-robust by construction and can be used for standard ICA as well as for overcomplete ICA (i.e. more source signals than observed signals). (c) 2005 Wiley Periodicals, Inc
Functional gait development in children is discussed controversially. Differentiated information about the roll- over process of the foot, represented by the "Center of Pressure" (COP), are still missing. The purpose of the study was the validation of the COP-path to quantify the functional gait development of children. Plantar pressure distribution was measured barefoot with an individual speed on a walkway (tartan) - in 255 children aged between 2 and 15 years. The medial and lateral area enclosed between the COP-path and the bisection of plantar angle (A(med), A(lat), Sigma: A(ml)) was calculated from plantar pressure data. Furthermore, the duration of the COP-path in the heel (COPtimeF), midfoot (COPtimeM) and forefoot (COPtimeV) was analysed. The load distribution under the medial and lateral forefoot was also calculated. The variation coefficient (VC) was calculated as a measure of interindividual variability. The medio-lateral divergency of the COP (Aml) initially decreases with advancing age (-20.2%), followed by a continuous increase (+27.2%). No changes in VC (A(med), A(lat), and A(ml)) appeared during age-related development. COPtimeM remains constant in all children over time. In contrast to COPtimeM, Cop(time)F decreases from youngest to oldest children (-31.0%), and COPtimeV increases (+41.7%). After initial descent up to 8 years of age, VC (COPtimeF, COPtimeM, COPtimeV) remains constant. The mediolateral load under the forefoot did not change. The COP-Path is able to characterise the functional gait development of children. VC values indicate high individual variability of gait pattern. In this context, age-based standard values should be critically discussed
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
We propose simple and fast methods based on nearest neighbors that order objects from high-dimensional data sets from typical points to untypical points. On the one hand, we show that these easy-to-compute orderings allow us to detect outliers (i.e. very untypical points) with a performance comparable to or better than other often much more sophisticated methods. On the other hand, we show how to use these orderings to detect prototypes (very typical points) which facilitate exploratory data analysis algorithms such as noisy nonlinear dimensionality reduction and clustering. Comprehensive experiments demonstrate the validity of our approach.