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Radar-Based Hand Gesture Recognition Using Spiking Neural Networks
2021
Electronics
We propose a spiking neural network (SNN) approach for radar-based hand gesture recognition (HGR), using frequency modulated continuous wave (FMCW) millimeter-wave radar. After pre-processing the range-Doppler or micro-Doppler radar signal, we use a signal-to-spike conversion scheme that encodes radar Doppler maps into spike trains. The spike trains are fed into a spiking recurrent neural network, a liquid state machine (LSM). The readout spike signal from the SNN is then used as input for
doi:10.3390/electronics10121405
fatcat:vasb26pc7zdpzj23cqdx6f5zzy