Time Series Analysis Using Entropy Metrics
Journal Title: Acta Marisiensis. Seria Technologica - Year 2017, Vol 14, Issue 1
Abstract
Entropy metrics are valuable tools for use in systems science and engineering. Both of domains are assumed to work with signals, to perform testing and evaluation tasks through specific signals. Entropy metrics indicate the degree of order/disorder in any given system, so they are capable to distinguish deterministic features from noise or chaos. The motivation of this paper is to present the main components and actual developments in entropy metrics used to analyze discrete time signals. The entropy metrics and measurements developed in this work try to find regularity in discrete time series in order to inspect them or predict future events.
Authors and Affiliations
Zoltán GERMÁN-SALLÓ, Horațiu-Ștefan GRIF
Keywords
Related Articles
- EP ID EP294244
- DOI -
- Views 132
- Downloads 0
Experimental Model for a Brake Test Stand
A brake test stand is a mechanical system that simulates a driveway in order to test the efficiency of the braking system of an auto vehicle. It hosts a range of sensors and transmitters which measure the braking forces...
Experiments of Controlers Tuning Based on Integral Criteria
For a system specified by the process, actuator and transducer, the obtaining of a certain operating regime (stationary and transient) is conditioned by the proper choice of a controller’s structure and the tuning parame...
What Does Engineering Ethics Involve?
This paper aims at elucidating and concluding information on engineering ethics, rights of engineers versus employee rights. This theoretical objective was achieved by the bibliographic study of some reference works in t...
Internet of Things Based on HTTP
This paper proposes using HTTP in the context of IoT, as a liaison between an ever-growing number of devices, standards and requirements. IoT devices are often resource-limited and do not support complex protocols. This...
The Complex Version of a Result for Real Iterative Functions
The purpose of this paper is to show a complex version for complex iterative functions of a result for real iterative functions and to give some applications for complex nonlinear equations.