Anytime information processing based on fuzzy and neural network models

In modern measurement and control systems, the available time and resources are often not only limited, but could change during the operation of the system. In these cases, the so called anytime algorithms could be used advantageously. While different soft computing methods are in widespread use in system modeling, their usability in these cases are limited, because the lack of a universal method for the determination of the needed complexity often results in huge and redundant neural networks/fuzzy rule-bases. This paper proposes a possible way to carry out anytime information processing in fuzzy systems or neural networks, with the help of the SVD-based complexity reduction algorithm.