36 citations · 96 across the 10 of their papers we have counts for
5 papers · 1 filter
Neural-HAR: A Dimension-Gated CNN Accelerator for Real-Time Radar Human Activity Recognition
Yizhuo Wu, Francesco Fioranelli, Chang Gao
Radar-based human activity recognition (HAR) is attractive for unobtrusive and privacy-preserving monitoring, yet many CNN/RNN solutions remain too heavy for edge deployment, and e…
OpenDPDv2: A Unified Learning and Optimization Framework for Neural Network Digital Predistortion
Yizhuo Wu, Ang Li, Chang Gao
Neural network (NN)-based Digital Predistortion (DPD) improves linearization for wideband radio frequency (RF) power amplifiers (PAs) but often increases the complexity of the digi…
TCN-DPD: Parameter-Efficient Temporal Convolutional Networks for Wideband Digital Predistortion
Huanqiang Duan, Manno Versluis, Qinyu Chen +2
Digital predistortion (DPD) is essential for mitigating nonlinearity in RF power amplifiers, particularly for wideband applications. This paper presents TCN-DPD, a parameter-effici…
DeltaDPD: Exploiting Dynamic Temporal Sparsity in Recurrent Neural Networks for Energy-Efficient Wideband Digital Predistortion
Yizhuo Wu, Yi Zhu, Kun Qian +5
Digital Predistortion (DPD) is a popular technique to enhance signal quality in wideband RF power amplifiers (PAs). With increasing bandwidth and data rates, DPD faces significant…
MP-DPD: Low-Complexity Mixed-Precision Neural Networks for Energy-Efficient Digital Predistortion of Wideband Power Amplifiers
Yizhuo Wu, Ang Li, Mohammadreza Beikmirza +5
Digital Pre-Distortion (DPD) enhances signal quality in wideband RF power amplifiers (PAs). As signal bandwidths expand in modern radio systems, DPD's energy consumption increasing…