Time-Series LPI Signal Classification and Relevance Analysis Using BiLSTM-Attention with LRP

This study applies a BiLSTM-Attention model and Layer-wise Relevance Propagation (LRP) to classify and analyze the importance of low probability of intercept (LPI) signals. The goal is to interpret the predictions of a time-series trained model using LRP and effectively identify meaningful input features. The analysis shows that the model main<span style=color:#999999 > ... </span><a href=javascript:; onclick=onClickReadNode('NODE12003205');fn_statistics('Z354','null','null'); style='color:#999999;font-size:14px;text-decoration:underline;' >전체 초록 보기</a>