scholarly journals Complex-valued time series modeling for improved activation detection in fMRI studies

2018 ◽  
Vol 12 (3) ◽  
pp. 1451-1478 ◽  
Author(s):  
Daniel W. Adrian ◽  
Ranjan Maitra ◽  
Daniel B. Rowe
Keyword(s):  
Time Series ◽  
Time Series Modeling ◽  
Activation Detection ◽  
Complex Valued

NARX Network based Driver Behavior Analysis and Prediction using Time-series Modeling

2018 ◽  
Vol 24 (3) ◽  
pp. 633-642
Author(s):  
Ling Wu ◽  
Haoxue Liu ◽  
Tong Zhu ◽  
Yueqi Hu
Keyword(s):  
Time Series ◽  
Behavior Analysis ◽  
Driver Behavior ◽  
Time Series Modeling

Meta-Analysis and Time Series Modeling Allow a Systematic Review of Primary HIV-1 Drug-Resistant Prevalence in Latin America and Caribbean

2015 ◽  
Vol 13 (2) ◽  
pp. 125-142 ◽  
Author(s):  
Antonio Coelho ◽  
Ronald Moura ◽  
Ronaldo Silva ◽  
Anselmo Kamada ◽  
Rafael Guimaraes ◽  
...  
Keyword(s):  
Systematic Review ◽  
Time Series ◽  
Latin America ◽  
Meta Analysis ◽  
Drug Resistant ◽  
Time Series Modeling ◽  
Latin America And Caribbean ◽  
Hiv 1

scholarly journals Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling

2021 ◽  
Vol 48 (4) ◽  
pp. 37-40
Author(s):  
Nikolas Wehner ◽  
Michael Seufert ◽  
Joshua Schuler ◽  
Sarah Wassermann ◽  
Pedro Casas ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Recurrent Neural Networks ◽  
Quality Of Experience ◽  
Unique Feature ◽  
Time Series Modeling ◽  
Web Browsing ◽  
Large Dataset ◽  
Efficient Approximation

This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-measurement platforms on different device-types, a unique feature set is designed and used to estimate the RUMSI - an efficient approximation to SI, with machinelearning based regression and classification approaches. Results indicate that it is possible to estimate the RUMSI accurately, and that in particular, recurrent neural networks are highly suitable for the task, as they capture the network dynamics more precisely.

AR and ARMA model order selection for time-series modeling with ImageNet classification

2021 ◽  
Vol 183 ◽  
pp. 108026
Author(s):  
Jihye Moon ◽  
Md Billal Hossain ◽  
Ki H. Chon
Keyword(s):  
Time Series ◽  
Arma Model ◽  
Order Selection ◽  
Time Series Modeling ◽  
Model Order Selection ◽  
Model Order ◽  
Selection For

Nonlinear Time Series Modeling and Forecasting for Periodic and ARCH Effects

2010 ◽  
Vol 4 (1) ◽  
pp. 27-44 ◽  
Author(s):  
Himadri Ghosh ◽  
Ranjit Kumar Paul ◽  
Prajneshu
Keyword(s):  
Time Series ◽  
Nonlinear Time Series ◽  
Time Series Modeling ◽  
Modeling And Forecasting

Fractional Field Image Time Series Modeling and Application to Cyclone Tracking

2021 ◽  
pp. 145-165
Author(s):  
Abdourrahmane M. Atto ◽  
Aluísio Pinheiro ◽  
Guillaume Ginolhac ◽  
Pedro Morettin
Keyword(s):  
Time Series ◽  
Time Series Modeling ◽  
Cyclone Tracking

Discussion of “Time Series Modeling of Chicago Particulates”

1980 ◽  
Vol 106 (3) ◽  
pp. 678-679
Author(s):  
Sivajogi D. Koppula
Keyword(s):  
Time Series ◽  
Time Series Modeling
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