Tensor-guided interpolation for off-grid power spectrum map construction
This paper addresses the off-grid tensor-guided interpolation problem, aiming to reconstruct
a 3D power spectrum map from sparse observations. A segmented polynomial model is …
a 3D power spectrum map from sparse observations. A segmented polynomial model is …
Data-Driven and Knowledge-Guided Heterogeneous Graphs and Temporal Convolution Networks for Flood Forecasting
Data-driven models have been successfully applied to flood prediction. However, the
nonlinearity and uncertainty of the prediction process and the possible noise or outliers in …
nonlinearity and uncertainty of the prediction process and the possible noise or outliers in …
Integrated Interpolation and Block-term Tensor Decomposition for Spectrum Map Construction
This paper addresses the challenge of reconstructing a 3D power spectrum map from
sparse, scattered, and incomplete spectrum measurements. It proposes an integrated …
sparse, scattered, and incomplete spectrum measurements. It proposes an integrated …
Tensor-Based Traffic Recovery of Industrial Network by BCD-Inspired Neural Approximation to Latent Nonlinearity and Sparsity
G Yue, Z Sun, J Fan - IEEE Transactions on Emerging Topics in …, 2023 - ieeexplore.ieee.org
Due to the massive network data created by the industrial Internet of Things, tensor as the
compact and multi-dimensional representation is widely employed to model the industrial …
compact and multi-dimensional representation is widely employed to model the industrial …
Energy-modified Leverage Sampling for Radio Map Construction via Matrix Completion
This paper explores an energy-modified leverage sampling strategy for matrix completion in
radio map construction. The main goal is to address potential identifiability issues in matrix …
radio map construction. The main goal is to address potential identifiability issues in matrix …