The topic of privacy-preserving big data analytics is gaining momentum now, thanks to the
plethora of modern application scenarios where it can be successfully applied. These range …

This paper introduces a new series of methods which combine modal decomposition
algorithms, such as singular value decomposition and high-order singular value …

This paper considers problems related to output error models for output data estimation and
parameter identification in missing output data systems. In this regard, a new sequentially …

Image processing is becoming increasingly important as imaging technology has advanced.
A storage constraint might occur even when image quality is an influential factor. This means …

The use of multivariate time series is often impeded by the discontinuity of key missing
features. In social networks, the absence of individual sentiment attributes presents …

Random projection can reduce the dimension of data while capturing its structure and is a
fundamental tool for machine learning, signal processing, and information retrieval, which …

Predicting wind and temperature fields around military vehicles during extended missions is
crucial to avoid detectability by infrared (IR) devices. Also, the abrupt shifting of wind …

In this work, we introduce a randomized algorithm for analyzing and capturing multi-linear
data structure. Tensor singular value decomposition (T-SVD) is a useful method to extract …