For vector sensors (VSs) comprising multiple components, quaternion embedding (QE) is a promising modeling approach that provides an elegant algebraic representation and captures cross-component correlations. In particular, the quaternion formalism facilitates diverse signal models. By coupling this advantage with the...
Yi Lou, Xing-Hao Qu, Yang Yang et al.· IEEE Transactions on Signal...· 0 citations
Recent years have witnessed a growing interest in AI-aided Kalman filters. While emerging methodologies, such as KalmanNet, were shown to facilitate tracking in partially known state-space models, they are not directly applicable when the underlying dynamics is unknown. To overcome this limitation, we extend the Kalman...
Mintaek Oh, Jeonghun Park, Nir Shlezinger et al.· 0 citations
Over-the-air computation has emerged as a scalable and efficient solution for deploying federated learning algorithms in wireless networks by exploiting waveform superposition for simultaneous model aggregation. Most existing work struggles with heterogeneous fading channels. These approaches either enforce unbiased up...
Ming Xiang, Nicolò Michelusi, Y. Eldar et al.· 0 citations
A learning-based framework is proposed to replace this MCMC step by reformulating both Gibbs updates as Gaussian denoising problems and implementing them through ODE diffusion, resulting in an alternative to MCMC-based split Gibbs at lower likelihood-update cost.
Yi Zhang, Rui Guo, Meng-Chu Xu et al.· 0 citations
This tutorial presents a comprehensive treatment of LAWNs from the joint perspectives of artificial intelligence (AI) and signal processing, and highlights opportunities for LAWNs to evolve into dependable, AI-native infrastructure for the intelligent skies.
Wei-Jie Yuan, Geng Sun, Jia-Cheng Wang et al.· IEEE Journal on Selected Top...· 0 citations
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