In particular, the technique of empirical mode decomposition is performed on the non-stationary received signal, and further converted into a grey-scale image. Then a convolutional neural network is applied for feature extraction and emitter identification.
Jun 4, 2021
The results show that the instantaneous frequency estimates generated by the EMD method are more accurate than those obtained by the Wavelet technique.
T. INTRODUCTION. Specific emitter identification (SEI) designates the unique transmitter of a given signal, using only external.
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The results show that the instantaneous frequency estimates generated by the EMD method are more accurate than those obtained by the Wavelet technique. read ...
A novel specific emitter identification method based on transient communication signal's time-frequency-energy distribution obtained by Hilbert-Huang ...
A novel SEI system for the common communication signals is introduced using empirical mode decomposition (EMD) method to separate components of a signal, ...
In this paper, we propose a joint variational modal decomposition (JVMD) algorithm, which is an improved version of VMD by simultaneously implementing modal ...
Our proposed method has three major steps: received signal decomposition using VMD, feature extraction, and emitter identification. We evaluate the performance ...
May 18, 2017 · This paper introduces a novel SEI system for the common communication signals. Empirical mode decomposition (EMD) method is applied in such system to separate ...
Jan 3, 2024 · For the VMD algorithm, the decomposition of each frame is performed ... identification based on variational mode decomposition and spectral.