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- Helge J. Ritter, Thomas Martinetz, Klaus Schulten
- Computation and neural systems series
- 1992

- Matthias Kaper, Peter Meinicke, Ulf Großekathöfer, Thomas Lingner, Helge J. Ritter
- IEEE Trans. Biomed. Engineering
- 2004

We propose an approach to analyze data from the P300 speller paradigm using the machine-learning technique support vector machines. In a conservative classification scheme, we found the correct solution after five repetitions. While the classification within the competition is designed for offline analysis, our approach is also well-suited for a real-world… (More)

- H. Ritter, T. Kohonen
- Biological Cybernetics
- 2004

Self-organized formation of topographic maps for abstract data, such as words, is demonstrated in this work. The semantic relationships in the data are reflected by their relative distances in the map. Two different simulations, both based on a neural network model that implements the algorithm of the selforganizing feature maps, are given. For both, an… (More)

- Alexander Lenhardt, Matthias Kaper, Helge J Ritter
- IEEE transactions on neural systems and…
- 2008

The P300 component of an event related potential is widely used in conjunction with brain-computer interfaces (BCIs) to translate the subjects intent by mere thoughts into commands to control artificial devices. A well known application is the spelling of words while selection of the letters is carried out by focusing attention to the target letter. In this… (More)

In this paper we present results of a study on brain computer interfacing. We adopted an approach of Farwell & Donchin [4], which we tried to improve in several aspects. The main objective was to improve the transfer rates based on offline analysis of EEG-data but within a more realistic setup closer to an online realization than in the original studies.… (More)

- Helge Ritter
- 1999

We propose a new type of Self-Organizing Map (SOM) that is based on discretizations of curved, non-euclidean spaces. As an introductory example, we brieey discuss \spherical SOMs" on tesselations of the sphere for the display of directional data. We then describe the construction of \hyperbolic SOMs", using regular tesselations of the hyperbolic plane,… (More)

- Claudia Nölker, Helge J. Ritter
- IEEE Trans. Neural Networks
- 2002

This paper describes GREFIT (Gesture REcognition based on FInger Tips), a neural network-based system which recognizes continuous hand postures from gray-level video images (posture capturing). Our approach yields a full identification of all finger joint angles (making, however, some assumptions about joint couplings to simplify computations). This allows… (More)

- Helge J. Ritter
- IEEE Trans. Neural Networks
- 1991

It is shown that for a class of vector quantization processes, related to neural modeling, that the asymptotic density Q(x ) of the quantization levels in one dimension in terms of the input signal distribution P(x) is a power law Q(x)=C-P(x)(alpha ), where the exponent alpha depends on the number n of neighbors on each side of a unit and is given by… (More)

- Thomas Martinetz, Helge J. Ritter, Klaus Schulten
- IEEE Trans. Neural Networks
- 1990

An extension of T. Kohonen's (1982) self-organizing mapping algorithm together with an error-correction scheme based on the Widrow-Hoff learning rule is applied to develop a learning algorithm for the visuomotor coordination of a simulated robot arm. Learning occurs by a sequence of trial movements without the need for an external teacher. Using input… (More)

- Heiko Wersing, Jochen J. Steil, Helge J. Ritter
- Neural Computation
- 2001

We present a recurrent neural network for feature binding and sensory segmentation: the competitive-layer model (CLM). The CLM uses topographically structured competitive and cooperative interactions in a layered network to partition a set of input features into salient groups. The dynamics is formulated within a standard additive recurrent network with… (More)