This survey paper discusses the fundamentals of power systems modelling in the presence
of large amounts of converter-interfaced generation (CIG). By referring to real-life events …

This paper provides a multi-disciplinary overview of the research issues and achievements
in the field of Big Data and its visualization techniques and tools. The main aim is to …

Abstract The Lomb–Scargle periodogram is a well-known algorithm for detecting and
characterizing periodic signals in unevenly sampled data. This paper presents a conceptual …

Although very successfully used in conventional machine learning, convolution based
neural network architectures--believed to be inconsistent in function space--have been …

Although deep networks are typically used to approximate functions over high dimensional
inputs, recent work has increased interest in neural networks as function approximators for …

We propose a sampling theory for signals that are supported on either directed or undirected
graphs. The theory follows the same paradigm as classical sampling theory. We show that …

Future wireless systems will be characterized by a large range of possible uses cases. This
requires a flexible allocation of the available time-frequency resources, which is difficult in …

Most of the real-life signals are non-stationary in nature. The examples of such signals
include biomedical signals, communication signals, speech, earthquake signals, vibration …

Computing the amounts of light arriving from different directions enables a diffusely
reflecting surface to play the part of a mirror in a periscope—that is, perform non-line-of-sight …

It is well known that the trapezoidal rule converges geometrically when applied to analytic
functions on periodic intervals or the real line. The mathematics and history of this …