13115995
Neural gas sonification - growing adaptive interfaces for interacting with data
In This work we present an approach using incrementally constructed neural gas networks to 'grow' an intuitive interface for interactive exploratory sonification of high-dimensional data. The sonifications portray information about the intrinsic data dimensionality and its variation within the data space. The interface follows the paradigm of model-based sonification and consists of a graph of nodes that can be acoustically 'excited' with simple mouse actions. The sound generation process is defined in terms of the node parameters and the graph topology, following a physically motivated model of energy flow through the graph structure. The resulting sonification model is tied to the given data set by constructing both graph topology and node parameters by an adaptive, fully data-driven learning process, using a growing neural gas network. We report several examples of applying this method to static data sets and point out a generalization to the task of process analysis.
5682288
Guest Editors' Introduction: An Introduction to Interactive Sonification
The research field of sonification, a subset of the topic of auditory display, has developed rapidly in recent decades. It brings together interests from the areas of data mining, exploratory data analysis, human-computer interfaces, and computer music. Sonification presents information by using sound (particularly nonspeech), so that the user of an auditory display obtains a deeper understanding of the data or processes under investigation by listening.
36348317
Identification of discriminative features in the EEG
An important step for the correlation of EEG signals with cognitive processes is the identification of discriminative features in the EEG signal. In this paper we utilize independent component analysis (ICA) for feature extraction and selection. Our specific ICA technique is based on a nonparametric source representation which in particular allows for modelling of multimodal feature distributions as generally required for the analysis of mixed data from different experiment conditions. To demonstrate the potential of the resulting ICA feature selection scheme we report results from an analysis of psycholinguistic experiments on the discrimination of speech perception from perception of so-called pseudo speech signals and demonstrate how the obtained ICA features can be further analyzed with the technique of sonification. Our results correlate well with results from coherence analysis and strongly indicate that these new methods are well suited for uncovering cognitively relevant features in EEG signals.
40071496
tacTilesfor Ambient Intelligence and Interactive Sonification
In this paper we introduce tacTiles, a novel wireless modular tactile sensitive surface element attached to a deformable textile, designed as a lay-on for surfaces such as chairs, sofas, floor or other furniture. tacTilescan be used as interface for human-computer interaction or ambient information systems. We give a full account on the hardware and show applications that demonstrate real-time sonification for process monitoring and biofeedback. Finally we sketch ideas for using tacTiles paired with sonification for interaction games.
5897687
Polyrhythmic organization of coupled nonlinear oscillators
We study the rhythmic organization of coupled nonlinear oscillators. If oscillators with non-identical internal frequency are coupled, they generate a great variety of periodic and chaotic rhythmic patterns. Sonification of these patterns suggests their characterization in terms of polyrhythms: each oscillatory unit subdivides "measures" of equal or varying length differently. For the case of two coupled oscillators, the organization of these polyrhythms is exemplified as a function of the internal frequency ratio and the coupling strength. Some sonification strategies are presented which aid to detect complex rhythmic relationships between oscillators. The results may be of importance for the analysis of complex multivariate time series like human EEG.
944953
The Sonification of Rhythms in Human Electroencephalogram
We use sonification of temporal information extracted from scalp EEG to characterize the dynamic properties of rhythms in certain frequency bands. Sonification proves particularly useful in the simultaneous monitoring of several EEG channels. Our results suggest sonification as an important tool in the analysis of multivariate data with subtle correlation differences.
23819859
Curve and surface design: H. Hagen (Ed.) SIAM, USA (1992), 219 pp, ISBN 089871-281-5
40714140
The guide RNA database
Guide RNAs (gRNAs) are small, metabolically stable RNA molecules which perform a pivotal, template-like function during the RNA editing process in kinetoplastid protozoa. The gRNA database currently contains 250 guide RNA sequences as well as secondary and tertiary structure models and other relevant information. The database is made available as a hypertext document accessible via the World Wide Web (WWW) at the URL: http://www.biochem.mpg.de/ goeringe/
42092183
Degree elevation for generalized Poisson functions
In this note a common generalization is given for the Bezier and Poisson functions. Further it is proved that the degree elevated control polygon converges to the function.
8720995
On the derivatives of second and third degree rational Bézier curves
In this note, an estimate of Floater on the derivatives of rational Bezier curves is improved when the degree of the curve is 2 or 3.
19159245
Improving and Extending the Lim/Lee Exponentiation Algorithm
. In [5] Lim and Lee present an algorithm for fast exponentiation in a given group which is optimized for a limited amount of storage. The algorithm uses one precomputation for several computations in order to minimize the average time needed for one exponentiation. This paper generalizes the previous work proposing several improvements and a method for fast precomputation. The basic Lim/Lee algorithm is improved by determining the optimal segmentation of the exponent. Finally, it is shown that the improved Lim/Lee algorithm is faster than the previous one in average case.