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Intelligent Recognition Method of Short Wave Communication Transmission Signal Based on the Blind Separation Algorithm

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Abstract

The traditional signal recognition method can not be quickly and efficiently identified by noise interference. In order to avoid the drawbacks of traditional methods, an intelligent identification method for short-wave communication transmission signals based on blind separation algorithm is proposed. According to the mathematical model, all the transmission signals in short-wave communication are modally decomposed, and the signal can be decomposed into functions of several different feature scales, and the time and frequency are extracted as the physical quantities of the signal characteristics. The blind separation algorithm is used for signal preprocessing. The short-time energy, short-term average amplitude and short-time zero-crossing rate are used as the starting point of the recognized speech signal. Under the fixed background noise, the normal signal and the noise signal are identified. It can be seen from the experimental results that the method has short recognition time and fast rate, which lays a foundation for short-wave communication transmission.

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Authors and Affiliations

  1. Liaoning Petrocchemical Vocational and Technology, Jinzhou, China

    Yan-song Hu

Authors
  1. Yan-song Hu
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Corresponding author

Correspondence to Yan-song Hu .

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Editors and Affiliations

  1. Nanjing University, Nanjing, China

    Guan Gui

  2. Harbin Engineering University, Harbin, China

    Lin Yun

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Hu, Ys. (2019). Intelligent Recognition Method of Short Wave Communication Transmission Signal Based on the Blind Separation Algorithm. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 301. Springer, Cham. https://doi.org/10.1007/978-3-030-36402-1_50

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  • DOI: https://doi.org/10.1007/978-3-030-36402-1_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36401-4

  • Online ISBN: 978-3-030-36402-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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