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Immunocomputing for intelligent signal processing

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Abstract

Based on immunocomputing (IC), this paper describes an approach to intelligent signal processing. The approach includes both low-level feature extraction and high-level (intelligent) pattern recognition. The key model is the formal immune network (FIN), which includes apoptosis (programmed cell death) and immunization and controls them by cytokines (messenger proteins). Such FIN can be formed from the signal or combination of signals using discrete tree transform, singular value decomposition and the proposed index of inseparability as a measure of quality of FIN. Several comparisons with neural computing and support vector machines suggest that IC may outperform state of the art approaches to intelligent signal processing.

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Authors and Affiliations

  1. St. Petersburg Institute for Informatics and Automation, Russian Academy of Sciences, 14-Line 39, St. Petersburg, 199178, Russia

    Alexander O. Tarakanov

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  1. Alexander O. Tarakanov
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Correspondence to Alexander O. Tarakanov.

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Tarakanov, A.O. Immunocomputing for intelligent signal processing. Neural Comput & Applic 19, 1143–1152 (2010). https://doi.org/10.1007/s00521-010-0391-7

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  • DOI: https://doi.org/10.1007/s00521-010-0391-7

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