Open access
Aug 2026
An energy-efficient spiking neural network accelerator on FPGA for real-time health monitoring of rotating machinery
An efficient diagnostic framework based on a field-programmable gate array (FPGA)-accelerated SNN integrating local spike-timing-dependent plasticity and global backpropagation through time is proposed, outperforming existing lightweight convolutional neural network-FPGA acceleration schemes.
Ke-Hui Zhu, Jin-Rui Zhang, Xin-Ming Li et al.
· Structural Health Monitoring · 0 citations