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Construction of fault-tolerant signal feature subsets

  • Representation, Processing, Analysis and Understanding of Images
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Abstract

New kinds of regularities in knowledge, viz., fault-tolerant signal-feature subsets, are proposed for use in intelligent test-pattern-recognition systems; the change in the values of these features indicates the transition of objects from one pattern to another. The algorithms for finding fault-tolerant signal-feature subsets are described and examples of their work are given. The algorithms for finding new regularities are implemented in a subsystem incorporated into the IMSLOG intelligent software tool based on test methods of pattern recognition. Examples from various problem domains are given to find subsets of signal features that are tolerant to measurement errors. The usability of these subsets is substantiated.

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Author information

Authors and Affiliations

  1. Tomsk National Research State University, Tomsk, Russia

    A. E. Yankovskaya

  2. Tomsk State University of Architecture and Building, Tomsk, Russia

    A. E. Yankovskaya & R. V. Ametov

  3. Tomsk State University of Control Systems and Radioelectronics, Tomsk, Russia

    A. E. Yankovskaya

  4. Siberian State Medical University, Tomsk, Russia

    A. E. Yankovskaya

Authors
  1. A. E. Yankovskaya
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  2. R. V. Ametov
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Correspondence to A. E. Yankovskaya.

Additional information

This paper uses the materials of a report that was submitted at the 11th International Conference Pattern Recognition and Image Analysis: New Information Technologies that was held in Samara, Russia on September 23–28, 2013.

Anna Efimovna Yankovskaya. Born in 1939. Graduated from the Tomsk State University in 1961. Received candidate’s degree in 1969 and doctoral degree in 2001. Head of the Laboratory of Intelligent Systems of the Tomsk State University of Architecture and Building, Professor at the Department of Applied Mathematics of the Tomsk State University of Architecture and Building, Professor at the Department of Program Engineering of the Tomsk State University, and Professor at the Department of Computer Systems for Control and Designing of the Tomsk State University of Control Systems and Radioelectronics, professor at the Department of Clinical Psychology and Psychiatry of the Siberian State Medical University. Scientific interests: mathematical basis of pattern recognition; theory of discrete control devices; logical tests for various problem and cross-disciplinary domains; logical-combinatorial, logical-combinatorial-probabilistic and genetic algorithms; intelligent systems based on test methods of pattern recognition; cognitive graphics; and cognitive modeling. Author of more than 640 publications, including 7monographs and 370 papers. Chairman of the Tomsk Regional Division of the Russian Association for Artificial Intelligence and the Tomsk Regional Division of the Russian Association for Pattern Recognition and Image Analysis. Member of the European Academy of Natural History. Twice (in 1999 and 2002) awarded the title “Winner of the Tomsk Region prize in the field of education and science.” Awarded the laureate diploma of the KII-94 exhibition “Software tools and systems of AI” in 1994. Awarded the Intel diploma of the competition of research projects in the field of automated design of integrated circuits in 2003.

Rinat Vinurovich Ametov. Born in 1977. Graduated from the Tomsk Polytechnic University in 1999. Deputy Director of the Center of Information Technologies of the Tomsk State University of Architecture and Building. Scientific interests: artificial intelligence, pattern recognition, data mining, intelligent systems. Author of 62 papers.

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Yankovskaya, A.E., Ametov, R.V. Construction of fault-tolerant signal feature subsets. Pattern Recognit. Image Anal. 25, 111–116 (2015). https://doi.org/10.1134/S1054661815010216

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  • DOI: https://doi.org/10.1134/S1054661815010216

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