4 papers
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…
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…
RadMamba: Efficient Human Activity Recognition through Radar-based Micro-Doppler-Oriented Mamba State-Space Model
Yizhuo Wu, Francesco Fioranelli, Chang Gao
Radar-based Human Activity Recognition (HAR) is an attractive alternative to wearables and cameras because it preserves privacy, and is contactless and robust to occlusions. Howeve…