D-Index & Metrics Best Publications

Andreas E. Kyprianou

University of Bath
United Kingdom

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Mathematics D-index 45 Citations 8,089 198 World Ranking 1025 National Ranking 76

Overview

What is he best known for?

The fields of study Andreas E. Kyprianou is best known for:

Distortion (music)
Amplifier
Artificial neural network

Wavelet and Wavelet transform are two areas of study in which Andreas E. Kyprianou engages in interdisciplinary research. In his papers, he integrates diverse fields, such as Wavelet transform and Wavelet packet decomposition. Andreas E. Kyprianou conducted interdisciplinary study in his works that combined Wavelet packet decomposition and Wavelet. As part of his studies on Partial discharge, Andreas E. Kyprianou often connects relevant subjects like Voltage. His study on Voltage is mostly dedicated to connecting different topics, such as Partial discharge. Electrical engineering and Amplifier are frequently intertwined in his study. His study brings together the fields of Computer network and Amplifier. In his articles, Andreas E. Kyprianou combines various disciplines, including Computer network and Telecommunications. He performs multidisciplinary studies into Telecommunications and Electronic engineering in his work.

His most cited work include:

Feature extraction of partial discharge signals using the wavelet packet transform and classification with a probabilistic neural network (118 citations)
Wavelet packet denoising for online partial discharge detection in cables and its application to experimental field results (51 citations)

What are the main themes of his work throughout his whole career to date

In his research, Multiplicative function, Uniqueness and Boundary (topology) is intimately related to Mathematical analysis, which falls under the overarching field of Differential equation. His research links Mathematical analysis with Boundary (topology). His Image (mathematics) study is focused on Similarity (geometry) and Noise (video). His research is interdisciplinary, bridging the disciplines of Image (mathematics) and Noise (video). His Nanotechnology study frequently involves adjacent topics like Characterization (materials science) and Layer (electronics). His Characterization (materials science) study frequently draws parallels with other fields, such as Optics. In his articles, he combines various disciplines, including Optics and Interferometry. His research links Nanotechnology with Layer (electronics). He integrates Artificial intelligence with Algorithm in his research.

Andreas E. Kyprianou most often published in these fields:

Artificial intelligence (72.73%)
Wavelet (54.55%)
Wavelet transform (36.36%)

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