Amazon cover image
Image from Amazon.com

Entropy Measures for Data Analysis: Theory, Algorithms and Applications

By: Material type: ArticleArticleLanguage: English Publication details: MDPI - Multidisciplinary Digital Publishing Institute 2019Description: 1 electronic resource (260 p.)ISBN:
  • books978-3-03928-033-9
  • 9783039280322
  • 9783039280339
Subject(s): Online resources: Summary: Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.
Item type:
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Home library Collection Call number Materials specified Status Date due Barcode
Electronic-Books Electronic-Books OPJGU Sonepat- Campus E-Books Open Access Available

Open Access star Unrestricted online access

Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.

Creative Commons https://creativecommons.org/licenses/by-nc-nd/4.0/ cc https://creativecommons.org/licenses/by-nc-nd/4.0/

English

There are no comments on this title.

to post a comment.

O.P. Jindal Global University, Sonepat-Narela Road, Sonepat, Haryana (India) - 131001

Send your feedback to glus@jgu.edu.in

Hosted, Implemented & Customized by: BestBookBuddies   |   Maintained by: Global Library