Study on fractal features of modulation signals

  • Lü T
  • Guo S
  • Xiao X
  • 4

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Abstract

Based on fractal theory, the note presents a novel method of modulation signals classification that adopts box dimension and information dimension extracted from received signals as features of classification. These features contain the characteristics of magnitude, frequency and phase of signals, and collect discriminatory information among various modulation modes. They are effective features in classification sense, and are insensitive to noises interfering. The theoretical analysis also proves the above conclusion. The classifier design is very simple based on such features. The simulation results show that the performances of signal classification are superior.

Author-supplied keywords

  • feature extracting
  • fractal
  • modulation recognition
  • modulation recognition of communication
  • noise interfere
  • of pattern recognition problem
  • signals is a kind

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Authors

  • Tiejun Lü

  • Shuangbing Guo

  • Xianci Xiao

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