Applications Based on Symmetry/Asymmetry in Functional Data Analysis

Dear Colleague,

Progress in science and technology, both in the collection and storage of data, is now providing us with datasets such as curves and surfaces or images instead of scalars or multivariate vectors. These kinds of datasets display infinite dimensional or functional features and are usually called functional datasets, which occur in chemometrics, engineering, phonetics, etc. Statistical methodologies handling functional data are methods for functional data analysis (FDA), which was first proposed by Ramsay in 1991. Then, Ramsay and Silverman published the monograph "Functional Data Analysis" in 1997. The failure of standard multivariate analysis, numerous application fields and the new theoretical challenges motivate the statistical community to develop new methods in FDA.

In this Special Issue of the prestigious journal Symmetry, we will highlight notable advances in FDA, including theories, methods and techniques, in the fields of mathematical analysis and functional analysis, in which the concept of symmetry plays an essential role. The main objective of this Special Issue is to bring together original research in statistical machine learning and data mining from academia, industry, others in a relaxed and stimulating atmosphere to focus on the development of theories, methods and applications of statistical learning in functional data.

Topics include, but are not limited to, FDA, big data analysis, classification, computational biology, covariance estimation, graphical models, high-dimensional data, learning theory, model selection, network data analysis, signal and image processing, etc.

Prof. Nengxiang Ling
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

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