The nature of statistical learning theory
The nature of statistical learning theory
WCET analysis for a Java processor
JTRES '06 Proceedings of the 4th international workshop on Java technologies for real-time and embedded systems
A Java processor architecture for embedded real-time systems
Journal of Systems Architecture: the EUROMICRO Journal
Predicting structured objects with support vector machines
Communications of the ACM - Scratch Programming for All
A real-time Java chip-multiprocessor
ACM Transactions on Embedded Computing Systems (TECS)
Parallel approaches to machine learning-A comprehensive survey
Journal of Parallel and Distributed Computing
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The term intelligent systems is spreading beyond the data mining and machine learning communities. This presents new challenges that are fundamental to classical problems within object oriented programming and analysis. In this paper we investigate the use of a popular intelligent algorithm on a Java-based processor. The processor is a real-time enabled processor implemented on an FPGA, and we deploy a support vector machine on this processor. Furthermore, we show how this support vector machine can work on the Java-processor's multiple cores. This is a first step toward understanding how intelligent algorithms can be implemented on object-oriented Java systems with multiple cores in a hard real-time environment. Our experiments show significant speedup of the selected machine learning algorithm, and this can potentially be useful for other intelligent algorithms also.