2 papers
eess.SP2026
Telling Neural Network What We Know: Weight Configuration for RNN and Its Application to NextG Real-Time Neural Receiver
Ummay Sumaya Khan, Lizhong Zheng, Lingjia Liu
AI-enabled receivers offer a promising approach to adaptive physical-layer processing, but conventional neural receivers often require extensive offline training and computationall…
cs.LG2026
When Learning Hurts: Fixed-Pole RNN for Real-Time Online Training
Alexander Morgan, Ummay Sumaya Khan, Lingjia Liu +1
Recurrent neural networks (RNNs) can be interpreted as discrete-time state-space models, where the state evolution corresponds to an infinite-impulse-response (IIR) filtering opera…