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 selforganization, 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 considered 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.

Self-descriptive IF THEN rules from signal measurements : a holonic-based computational technique / M. Calabrese - In: IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA 2010)[s.l] : IEEE, 2010. - ISBN 978-1-4244-7228-4. - pp. 102-106 (( convegno IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA 2010) tenutosi a Taranto nel 2010 [10.1109/CIMSA.2010.5611760].

Self-descriptive IF THEN rules from signal measurements : a holonic-based computational technique

M. Calabrese
Primo
2010

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 selforganization, 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 considered 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.
Granular computing; Holonic systems; IF THEN rules; Self-description; Signal measurements
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
IEEE
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/153476
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