Abstract: Conventional direction-of-arrival (DOA) estimation methods are sensitive to outlier measurements. Therefore, their performance may degrade substantially in the presence of impulsive noise.

Abstract: Federated learning (FL) allows multiple clients to collaboratively learn a globally shared model through cycles of model aggregation and local model training, without the need to share data.