Search Results for author:
Found 3 papers, 0 papers with code
Contrastive Psudo-supervised Classification for Intra-Pulse Modulation of Radar Emitter Signals Using data augmentation
The automatic classification of radar waveform is a fundamental technique in electronic countermeasures (ECM). Recent supervised deep learning-based methods have achieved great success in a such classification task. However, those methods require enough labeled samples to work properly and in many circumstances, it is not available. To tackle this problem, in this paper, we propose a three-stages deep radar waveform clustering(DRSC) technique to automatically group the received signal samples without labels. Firstly, a pretext model is trained in a self-supervised way with the help of several data augmentation techniques to extract the class-dependent features. Next, the pseudo-supervised contrastive training is involved to further promote the separation between the extracted class-dependent features. And finally, the unsupervised problem is converted to a semi-supervised classification problem via pseudo label generation.
Time-dependent Orbital-free Density Functional Theory: Background and Pauli kernel approximations
The dynamic Pauli potential and associated kernel emerge as key ingredients of time-tependent orbital-free DFT.
Chemical Physics
6 nm super-resolution optical transmission and scattering spectroscopic imaging of carbon nanotubes using a nanometer-scale white light source
Optical hyperspectral imaging based on absorption and scattering of photons at the visible and adjacent frequencies denotes one of the most informative and inclusive characterization methods in material research.
Super-Resolution
Optics
Materials Science
