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Clustering of Complex Electronic Systems with Self-Ordering Maps
Technical Paper
2005-01-1286
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
In this paper an approach to clustering of complex electronic systems using Self-Ordering Maps (SOMs) is presented. SOMs are neural networks which learn through a competitive learning algorithm. In order to use SOMs for the clustering of electronic networks, a representation of the communication behavior in n-dimensional space is developed. The SOM is then used as a nonlinear projection of this space onto a two-dimensional plane.
Two examples of clustering are given. The more complex of the two is verified by comparing the behavior of the clustered system and the unclustered system on a simple model of the CAN bus.
It is shown that SOMs can be used to effectively cluster complex electronic systems.
Authors
Citation
Nenninger, P., Rambow, T., and Kiencke, U., "Clustering of Complex Electronic Systems with Self-Ordering Maps," SAE Technical Paper 2005-01-1286, 2005, https://doi.org/10.4271/2005-01-1286.Also In
Automotive Electronics on CD-ROM from the SAE 2005 World Congress
Number: SP-1980CD; Published: 2005-04-11
Number: SP-1980CD; Published: 2005-04-11
SAE 2005 Transactions Journal of Passenger Cars: Electronic and Electrical Systems
Number: V114-7; Published: 2006-02-01
Number: V114-7; Published: 2006-02-01
References
- Nenninger P. Rambow T. Kiencke U. “ Automatic Model Based Partitioning of Distributed Automotive Electronic Systems ” SAE World Congress Detroit 2004
- Baccelli F. Cohen G. Olsder G.J. Quadrat J.-P. “ Synchronisation and Linearity ” Wilson 1992
- Kohonen T. “ Self-Organizing Maps ” Springer, Berlin 1995
- Neumann K. J. “ Partitionierung verteilter Echtzeitfunktionen in vernetzten Systemen ” Universität Karlsruhe 1997