Abstract
General functional decomposition has important application in many fields of modern engineering and science. Its practical usefulness for very complex systems is however limited by lack of an effective and efficient method for selection of the appropriate input supports for sub-systems. In this paper, an effective and efficient heuristic method for input support selection is proposed and discussed. The experimental results demonstrate that the method is able to construct optimal or near optimal supports efficiently even for large systems.
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© 1998 Springer-Verlag Berlin Heidelberg
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Rawski, M., Jóźwiak, L., Chojnacki, A. (1998). Application of the Information Measures to Input Support Selection in Functional Decomposition. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_79
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DOI: https://doi.org/10.1007/3-540-69115-4_79
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