The expectation-maximization (EM) algorithm is a cornerstone technique for parameter estimation in statistical models that incorporate latent variables or incomplete data. By iteratively alternating ...

Abstract: This letter proposes a low-complexity off-grid inverse-free sparse Bayesian learning (OG-IFSBL) algorithm for OTFS channel estimation that avoids computationally prohibitive matrix ...

Abstract: Influence maximization (IM) has garnered extensive attention due to its broad applicability across various real-world domains. However, most existing approaches primarily focus on the ...