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HOS Based Distinctive Features for Preliminary Signal Classification

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Independent Component Analysis and Blind Signal Separation (ICA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3195))

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Abstract

We consider the problem of preliminary classification of digitally modulated signals. The goal is to simplify further signal analysis (synchronization, signal separation, modulation identification and parameters estimation) by making initial separation among the most known classes of signals. Proposed methodology is mainly based on Higher Order Statistics (HOS) of the distributions of instantaneous amplitude and frequency. The experimental results emphasize the performance of the proposed set of features.

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Author information

Authors and Affiliations

  1. École Nationale Supérieure des Ingénieurs, des Études et Techniques d’Armement (ENSIETA), Laboratoire “Extraction et Exploitation de l’Information, en Environnements Incertains” (E3I2), Brest, France

    Maciej Pędzisz & Ali Mansour

Authors
  1. Maciej Pędzisz
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  2. Ali Mansour
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Editor information

Editors and Affiliations

  1. Dept. of Architecture and Computer Technology, University of Granada, Spain

    Carlos G. Puntonet  & Alberto Prieto  & 

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Pędzisz, M., Mansour, A. (2004). HOS Based Distinctive Features for Preliminary Signal Classification. In: Puntonet, C.G., Prieto, A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30110-3_146

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  • DOI: https://doi.org/10.1007/978-3-540-30110-3_146

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  • Print ISBN: 978-3-540-23056-4

  • Online ISBN: 978-3-540-30110-3

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