Citation: Marco Calabrese, Self-Descriptive IF THEN Rules from Signal Measurements. A holonic-based computational technique, 2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA 2010), Taranto, Italy, 6-8 September 2010, pp. 102-106, ISBN: 978-1-4244-7229-1
Abstract: A holon is a bio-inspired conceptual entity that, like cells in a living organism, behaves as a part and a whole at the same time. Holonic systems have been the subject of intense research in the latest years due to their properties such as self-organization, self-similarity and capability of handling hierarchically-nested granularity levels. Lesser attention indeed has been paid by engineers to the aspect of self-description, i. e. the ability to describe itself in terms of self-contained descriptors. Self-description can be useful in measurement settings where the only available knowledge is embedded in data in terms of hidden rules behind observed signals. In this work, a heuristic technique is employed to extract self-descriptive IF THEN rules from measurement signals. These rules are holonic in that they represent a whole described in terms of relationships among their parts. An example taken from a real measurement scenario is reported and commented in detail.
Keyword: holonic systems; self-description, signal measurements