Filters are fundamental in extracting information from data. For time series and image data
that reside on Euclidean domains, filters are the crux of many signal processing and …

The development of Internet of Things (IoT) technologies has led to the widespread adoption
of monitoring networks for a wide variety of applications, such as smart cities, environmental …

Gaps in the measurement series of atmospheric pollutants can impede the reliable
assessment of their impacts and trends. We propose a new method for missing data …

The development of contemporary artificial intelligence (AI) methods such as artificial neural
networks (ANNs) has given researchers around the world new opportunities to address …

This paper proposes a blind detection problem for low pass graph signals. Without
assuming knowledge of the exact graph topology, we aim to detect if a set of graph signal …

This paper proposes a robust adaptive algorithm for smooth graph signal recovery which is
based on generalized correntropy. A proper cost function is defined, which takes the …

Things receive digital intelligence by being connected to the Internet and by adding sensors.
With the use of real-time data and this intelligence, things may communicate with one …

The use of low-cost sensors in conjunction with high-precision instrumentation for air
pollution monitoring has shown promising results in recent years. One of the main …

This article is concerned with the outlier-resistant state estimation problem for industrial pipe
networks (PNs). PN signals, eg, pressure and temperature, are modeled as low-pass time …

Outliers are often present in data and many algorithms exist to find these outliers. Often we
can verify these outliers to determine whether they are data errors or not. Unfortunately …