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Abstract: We present a method for the unsupervised segmentation of data streams originating from different unknown sources which alternate in time. We use an architecture consisting of competing neural networks. Memory is included in order to resolve ambiguities of input-output relations. In order to obtain maximal specialization, the competition is adiabatically increased during training. Our method achieves almost perfect identification and segmentation in the case of switching chaotic dynamics where... (Update)
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BibTeX entry: (Update)
Pawelzik, K., Kohlmorgen, J. & Muller, K.-R. (1996). Annealed competition of experts for a segmentation and classification of switching dynamics. Neural Computation, 8(2), 340--356. http://citeseer.ist.psu.edu/pawelzik96annealed.html More
@article{ pawelzik96annealed,
author = "Klaus Pawelzik and Jens Kohlmorgen and Klaus-Robert Muller",
title = "Annealed Competition of Experts for a Segmentation and Classification of Switching Dynamics",
journal = "Neural Computation",
volume = "8",
number = "2",
pages = "340--356",
year = "1996",
url = "citeseer.ist.psu.edu/pawelzik96annealed.html" }
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