The literature on mixed-frequency models is relatively recent and has found applications
across economics and finance. The standard application in economics considers the use of …

Tensor Completion is an important problem in big data processing. Usually, data acquired
from different aspects of a multimodal phenomenon or different sensors are incomplete due …

In this paper, the problem of image super-resolution for Optical Coherence Tomography
(OCT) has been addressed. Due to the motion artifacts, OCT imaging is usually done with a …

Singular spectrum analysis (SSA) is the popular tool for analysing and forecasting time
series. SSA can be used for parametric estimation, forecasting and gap filling amongst many …

A fault or mechanical flaw causes several feeble swings in the position signal. Identification
of such swings by encoders can help to identify machine performance and health status and …

Singular spectrum analysis (SSA) is a nonparametric method for separating time series data
into a sum of small numbers of interpretable components (signal+ noise). One of the steps of …

Background: Heart rate variability (HRV) is derived from the series of RR intervals extracted
from an electrocardiographic (ECG) measurement. Ideally all components of the RR series …

Developments in data collecting efficiency in recent years have led to a rise in the quantity of
time series data in several areas of study such as finance, environmental science, and …

A fault or mechanical aw causes several feeble swings in the position signal. IdentiŻcation of
such swings by encoders can help to identify machine performance and health status and …

Missing values in time series data is a well-known and important problem which many
researchers have studied extensively in various fields. In this investigation, we propose a …