You are currently viewing a new version of our website. To view the old version click .

Entropy, Volume 24, Issue 8

August 2022 - 161 articles

Cover Story: In the article by Sabeti et al., a new information theoretic anomaly detector for time series is introduced. The method is based on detecting changes in the compressability of a test segment of the time series as measured by the difference between complexities of a typical encoder and a universal encoder. The typical and universal encoders are respectively implemented with a tree-structured pattern dictionary, trained on an earlier segment of the time series, and a Lempel–Ziv encoder. The anomaly detector is illustrated for a chaotic time series with model shift and for early detection of anomalous heart rates and skin temperatures of patients after exposure to a respiratory virus. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
  • You may sign up for email alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.

Articles (161)

  • Article
  • Open Access
6 Citations
2,337 Views
17 Pages

17 August 2022

We study the contrarian voter model for opinion formation in a society under the influence of an external oscillating propaganda and stochastic noise. Each agent of the population can hold one of two possible opinions on a given issue—against o...

  • Article
  • Open Access
2 Citations
3,326 Views
27 Pages

Community Detection in Semantic Networks: A Multi-View Approach

  • Hailu Yang,
  • Qian Liu,
  • Jin Zhang,
  • Xiaoyu Ding,
  • Chen Chen and
  • Lili Wang

17 August 2022

The semantic social network is a complex system composed of nodes, links, and documents. Traditional semantic social network community detection algorithms only analyze network data from a single view, and there is no effective representation of sema...

  • Article
  • Open Access
15 Citations
2,180 Views
16 Pages

Combine Harvester Bearing Fault-Diagnosis Method Based on SDAE-RCmvMSE

  • Guangyou Yang,
  • Yuan Cheng,
  • Chenbo Xi,
  • Lang Liu and
  • Xiong Gan

17 August 2022

In the fault monitoring of rolling bearings, there is always loud noise, leading to poor signal stationariness. How to accurately and efficiently identify the fault type of rolling bearings is a challenge. Based on multivariate multiscale sample entr...

  • Feature Paper
  • Article
  • Open Access
5 Citations
4,171 Views
16 Pages

17 August 2022

There has been a considerable amount of literature on binomial regression models that utilize well-known link functions, such as logistic, probit, and complementary log-log functions. The conventional binomial model is focused only on a single parame...

  • Article
  • Open Access
9 Citations
2,906 Views
20 Pages

Spatio-Temporal Dynamics of Entropy in EEGS during Music Stimulation of Alzheimer’s Disease Patients with Different Degrees of Dementia

  • Tingting Wu,
  • Fangfang Sun,
  • Yiwei Guo,
  • Mingwei Zhai,
  • Shanen Yu,
  • Jiantao Chu,
  • Chenhao Yu and
  • Yong Yang

17 August 2022

Music has become a common adjunctive treatment for Alzheimer’s disease (AD) in recent years. Because Alzheimer’s disease can be classified into different degrees of dementia according to its severity (mild, moderate, severe), this study i...

  • Article
  • Open Access
3,476 Views
45 Pages

Machine Learning Methods for Multiscale Physics and Urban Engineering Problems

  • Somya Sharma,
  • Marten Thompson,
  • Debra Laefer,
  • Michael Lawler,
  • Kevin McIlhany,
  • Olivier Pauluis,
  • Dallas R. Trinkle and
  • Snigdhansu Chatterjee

16 August 2022

We present an overview of four challenging research areas in multiscale physics and engineering as well as four data science topics that may be developed for addressing these challenges. We focus on multiscale spatiotemporal problems in light of the...

  • Article
  • Open Access
2 Citations
1,849 Views
11 Pages

16 August 2022

We show that neural networks with an absolute value activation function and with network path norm, network sizes and network weights having logarithmic dependence on 1/ε can ε-approximate functions that are analytic on certain region...

  • Article
  • Open Access
12 Citations
2,792 Views
18 Pages

Fault Diagnosis of Power Transformer Based on Time-Shift Multiscale Bubble Entropy and Stochastic Configuration Network

  • Fei Chen,
  • Wanfu Tian,
  • Liyao Zhang,
  • Jiazheng Li,
  • Chen Ding,
  • Diyi Chen,
  • Weiyu Wang,
  • Fengjiao Wu and
  • Bin Wang

16 August 2022

In order to accurately diagnose the fault type of power transformer, this paper proposes a transformer fault diagnosis method based on the combination of time-shift multiscale bubble entropy (TSMBE) and stochastic configuration network (SCN). Firstly...

  • Article
  • Open Access
2 Citations
1,916 Views
10 Pages

Research of the Algebraic Multigrid Method for Electron Optical Simulator

  • Zhi Wang,
  • Quan Hu,
  • Xiao-Fang Zhu,
  • Bin Li,
  • Yu-Lu Hu,
  • Tao Huang,
  • Zhong-Hai Yang and
  • Liang Li

16 August 2022

At present, electron optical simulator (EOS) takes a long time to solve linear FEM systems. The algebraic multigrid preconditioned conjugate gradient (AMGPCG) method can improve the efficiency of solving systems. This paper is focused on the implemen...

  • Feature Paper
  • Article
  • Open Access
1 Citations
1,980 Views
15 Pages

16 August 2022

We introduce a modern, optimized, and publicly available implementation of the sequential Information Bottleneck clustering algorithm, which strikes a highly competitive balance between clustering quality and speed. We describe a set of optimizations...

of 17

Get Alerted

Add your email address to receive forthcoming issues of this journal.

XFacebookLinkedIn
Entropy - ISSN 1099-4300Creative Common CC BY license