Wireless sensor network (WSN) is an emerging and promising developing area in the
intelligent sensing field. Due to various factors like sudden sensors breakdown or saving …

Unlike the flat-view matrix, tensor provides an elegant representation to preserve the
structure of data in the multidimensional nature. The wide use of tensor-based approaches …

This paper presents a novel probability-weighted tensor robust principal component
analysis (TRPCA) method based on CANDECOMP/PARAFAC decomposition (CPD) for …

Due to various restrictions, some Internet of Things (IoT) sensing layers can only deploy a
small number of sensor nodes for spatiotemporal low-resolution environmental information …

Recently, the low-rank tensor completion method based on tensor train (TT) rank has
achieved promising performance. Ket augmentation (KA) is commonly used in TT rank …

Technological developments coupled with socioeconomic changes are driving a rapid
transformation of the fifth-generation (5G) cellular network landscape. This evolution has led …

The Internet of Things data (IoT) with noise and substantial outliers are unavoidable, due to
imperfect communication environment. Tensor decomposition (TD)-based robust principal …

The emergence of the heterogeneous Internet of Things (IoT) has realized the demand for
multi-attribute data collection in response to the increasing demand for information in …

Restricted by various factors, the data collected by sensor nodes in some Internet of Things
(IoT) can only provide spatio-temporal low-resolution multi-attribute information of the …

Recent concerns in biomedical image processing revolve around robustly detecting outliers
and noise. A major challenge in emerging statistical and mathematical domains involves …