A recurrent spiking neural network accelerator achieves 71.2 μW real-time speech recognition on TSMC 28nm CMOS via 96.42% model compression and hardware techniques reducing complexity by 90.49%.
His research interests include VLSI design, com- puter architecture, and platform-based SoC design methodologies
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A 71.2-$\mu$W Speech Recognition Accelerator with Recurrent Spiking Neural Network
A recurrent spiking neural network accelerator achieves 71.2 μW real-time speech recognition on TSMC 28nm CMOS via 96.42% model compression and hardware techniques reducing complexity by 90.49%.