Stability of Markov chains on topological spaces with applications to adaptive control and time series analysis

2005 ◽  
pp. 369-401
Author(s):  
Sean P. Meyn
Keyword(s):  
Time Series ◽  
Adaptive Control ◽  
Time Series Analysis ◽  
Markov Chains ◽  
Topological Spaces ◽  
Series Analysis

scholarly journals Modelling and (adaptive) control of greenhouse climates.

1984 ◽  
Vol 32 (2) ◽  
pp. 137-139 ◽  
Author(s):  
A.J. Udink ten Cate
Keyword(s):  
Time Series ◽  
Adaptive Control ◽  
Time Series Analysis ◽  
Temperature Control ◽  
Control Process ◽  
Climate Control ◽  
Analysis Techniques ◽  
Series Analysis ◽  
Novel Approach ◽  
New Algorithms

After a discussion on control of greenhouse climates, new algorithms for temperature control are presented and tested in practice. A novel approach of modelling of the climate control process is presented by using time-series analysis techniques. (Abstract retrieved from CAB Abstracts by CABI’s permission)

Symbolic Time Series Analysis for Anomaly Detection in Measure-Invariant Ergodic Systems

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Najah F. Ghalyan ◽  
Asok Ray
Keyword(s):  
Experimental Data ◽  
Time Series ◽  
Time Series Analysis ◽  
Anomaly Detection ◽  
Markov Chains ◽  
Fatigue Damage ◽  
Superior Performance ◽  
Series Analysis ◽  
Time Invariant ◽  
Symbolic Time Series Analysis

Abstract This paper presents a novel framework of symbolic time series analysis (STSA) for anomaly detection in dynamical systems. The core concept is built upon a property of measure-preserving transformation (MPT) sequence, acting on a probability space with ergodic measure, that the eigenfunctions of these transformations would be time-invariant. As a result, unlike a standard STSA that is required to generate time-homogeneous Markov chains, the proposed MPT-based STSA is allowed to have time-inhomogeneous Markov chains, where the (possibly time-varying) state transition probability matrices have time-invariant eigenvectors. Such a time-invariance facilitates analysis of the dynamical system by using short-length time series of measurements. This is particularly important in applications, where the underlying dynamics and process anomalies need fast monitoring and control actions in order to mitigate any potential structural damage and/or to avoid catastrophic failures. The MPT-based STSA has been applied for low-delay detection of fatigue damage, which is a common source of failures in mechanical structures and which is known to have uncertain dynamical characteristics. The underlying algorithm has been validated with experimental data generated from a laboratory apparatus that uses ultrasonic sensors to detect fatigue damage in polycrystalline–alloy specimens. The performance of the proposed MPT-based STSA is evaluated by comparison with those of a standard STSA and a hidden Markov model (HMM) on the same experimental data. The results consistently show superior performance of the MPT-based STSA.

Review of Time Series Analysis: Regression Techniques (2nd ed.).

1991 ◽  
Vol 36 (4) ◽  
pp. 349-349
Author(s):  
No authorship indicated
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Series Analysis ◽  
Regression Techniques

Dynamical Peculiarities of Concatenational Changes in Functional Cardiovascular Parameters

2018 ◽  
Vol 3 (82) ◽  
Author(s):  
Eurelija Venskaitytė ◽  
Jonas Poderys ◽  
Tadas Česnaitis
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Functional State ◽  
The Body ◽  
Functional Changes ◽  
High Intensity Training ◽  
Series Analysis ◽  
Greco Roman ◽  
St Segment ◽  
Standard Lead

Research  background  and  hypothesis.  Traditional  time  series  analysis  techniques,  which  are  also  used  for the analysis of cardiovascular signals, do not reveal the relationship between the  changes in the indices recorded associated with the multiscale and chaotic structure of the tested object, which allows establishing short-and long-term structural and functional changes.Research aim was to reveal the dynamical peculiarities of interactions of cardiovascular system indices while evaluating the functional state of track-and-field athletes and Greco-Roman wrestlers.Research methods. Twenty two subjects participated in the study, their average age of 23.5 ± 1.7 years. During the study standard 12 lead electrocardiograms (ECG) were recorded. The following ECG parameters were used in the study: duration of RR interval taken from the II standard lead, duration of QRS complex, duration of JT interval and amplitude of ST segment taken from the V standard lead.Research  results.  Significant  differences  were  found  between  inter-parametric  connections  of  ST  segment amplitude and JT interval duration at the pre and post-training testing. Observed changes at different hierarchical levels of the body systems revealed inadequate cardiac metabolic processes, leading to changes in the metabolic rate of the myocardium and reflected in the dynamics of all investigated interactions.Discussion and conclusions. It has been found that peculiarities of the interactions of ECG indices interactions show the exposure of the  functional changes in the body at the onset of the workload. The alterations of the functional state of the body and the signs of fatigue, after athletes performed two high intensity training sessions per day, can be assessed using the approach of the evaluation of interactions between functional variables. Therefore the evaluation of the interactions of physiological signals by using time series analysis methods is suitable for the observation of these processes and the functional state of the body.Keywords: electrocardiogram, time series, functional state.

The Contribution of Foreign Direct Investment for Economic Growth of Ethiopia: Time Series Analysis

2018 ◽  
Vol 9 (02) ◽  
Author(s):  
Addissie Melak
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Foreign Direct Investment ◽  
Time Series Analysis ◽  
Direct Investment ◽  
Policy Framework ◽  
Annual Growth Rate ◽  
African Countries ◽  
Series Analysis ◽  
Integration Test

Economic growth of countries is one of the fundamental questions in economics. Most African countries are opening their economies for welcoming of foreign investors. As such Ethiopia, like many African countries took measures to attract and improve foreign direct investment. The purpose of this study is to examine the contribution of foreign direct investment (FDI) for economic growth of Ethiopia over the period of 1981-2013. The study shows an overview of Ethiopian economy and investment environment by the help of descriptive and econometric methods of analysis to establish empirical investigation for the contribution of FDI on Ethiopian economy. OLS method of time series analysis is employed to analyse the data. The stationary of the variables have been checked by using Augmented Dickey Fuller (ADF) Unit Root test and hence they are stationery at first difference. The co- integration test also shows that there is a long run relationship between the dependent and independent variables. Accordingly, the finding of the study shows that FDI, GDP per capita, exchange rate, total investment as percentage of GDP, inflow of FDI stock, trade as percentage of GDP, annual growth rate of GDP and liberalization of the economy have positive impact on Ethiopian GDP. Whereas Gross fixed domestic investment, inflows of FDI and Gross capital formation influence economic growth of Ethiopia negatively. This finding suggests that there should be better policy framework to attract and improve the volume of FDI through creating conducive environment for investment.

Quasi-Static Time-Series Analysis of Congested Transmission Networks with Intermittent Wind Power Penetration

2017 ◽  
Vol 12 (3) ◽  
pp. 237 ◽  
Author(s):  
Mohamed Abdel-Warth ◽  
Mamdouh Abdel-Akher ◽  
Mohamed M. Aly ◽  
Ahmad Eid
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Wind Power ◽  
Transmission Networks ◽  
Series Analysis
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