January 2010
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Kernel based classification, such as support vector machine, is often implemented and evaluated on powerful data processing systems. In this paper we deal with a new approach to process kernel based classification on processing systems with mathematical support on a lower level, in consequence of their operating system or typical application area, like PLC's. We investigate constrains of a PLC and what approximations are necessary for the implementation of feature extraction and classification. It will be shown that implementing a SVM on a PLC is possible because of their polynomial complexity.