Browse Publications Technical Papers 2005-01-1286

Clustering of Complex Electronic Systems with Self-Ordering Maps 2005-01-1286

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.


Subscribers can view annotate, and download all of SAE's content. Learn More »


Members save up to 43% off list price.
Login to see discount.
Special Offer: With TechSelect, you decide what SAE Technical Papers you need, when you need them, and how much you want to pay.