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 …

Federated learning (FL) is a promising paradigm to empower on-device intelligence in
Industrial Internet of Things (IIoT) due to its capability of training machine learning models …

Today's air pollution sensor networks pose new challenges given their heterogeneity of low-
cost sensors and high-cost instrumentation. Recently, with the advent of graph signal …

While frequency-domain algorithms have been demonstrated to be powerful for
conventional nonlinear signal processing, there is still not much progress in literature …

Recent years have seen the wide application of Location-Based Services (LBSs) in our daily
life. Although users can enjoy many conveniences from the LBSs, they may lose their …

The interconnection of instruments (ie, actuators and sensors) networked together for
industrial applications brings about the Industrial Internet of Things (IIoT). This connectivity …

Optimizing deep neural network (DNN) models to meet Quality of Service (QoS)
requirements in terms of accuracy and computation is of crucial importance for realizing …

Mobile crowdsensing enables people to collect and process a massive amount of
information by using social resources without any cost on sensor deployment or model …

The rapid urbanization and increasing structural complexities of modern buildings have
heightened the need for advanced monitoring systems to ensure building safety. The …