Knowledge-enhanced compressed measurements for detection of frequency-hopping spread spectrum signals based on task-specific information and deep neural networks

HIGHLIGHTS

• who: Feng Liu and Yinghai Jiang from the College of Electronic Information and Optical Engineering, Nankai University, Tianjin, China have published the research work: Knowledge-Enhanced Compressed Measurements for Detection of Frequency-Hopping Spread Spectrum Signals Based on Task-Specific Information and Deep Neural Networks, in the Journal: Entropy 2023, 25, 11. of /2023/
• what: The authors propose an efficient adaptive method to measure and detect the FHSS signals non-cooperatively. In this work, the training of the DNNs was conducted using the gradient-based backpropagation method. The authors provide Monte-Carlo simulation results to . . .
  

   

  

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