Chaotic Time Series Analysis
نویسنده
چکیده
Chaotic dynamical systems are ubiquitous in nature and most of them does not have an explicit dynamical equation and can be only understood through the available time series. We here briefly review the basic concepts of time series and its analytic tools, such as dimension, Lyapunov exponent, Hilbert transform, and attractor reconstruction. Then we discuss its applications in a few fields such as the construction of differential equations, identification of synchronization and coupling direction, coherence resonance, and traffic data analysis in Internet.
منابع مشابه
Chaotic Analysis and Prediction of River Flows
Analyses and investigations on river flow behavior are major issues in design, operation and studies related to water engineering. Thus, recently the application of chaos theory and new techniques, such as chaos theory, has been considered in hydrology and water resources due to relevant innovations and ability. This paper compares the performance of chaos theory with Anfis model and discusses ...
متن کاملModel Based Method for Determining the Minimum Embedding Dimension from Solar Activity Chaotic Time Series
Predicting future behavior of chaotic time series system is a challenging area in the literature of nonlinear systems. The prediction's accuracy of chaotic time series is extremely dependent on the model and the learning algorithm. On the other hand the cyclic solar activity as one of the natural chaotic systems has significant effects on earth, climate, satellites and space missions. Several m...
متن کاملRiver Discharge Time Series Prediction by Chaos Theory
The application of chaos theory in hydrology has been gaining considerable interest in recent years.Based on the chaos theory, the random seemingly series can be attributed to deterministic rules. Thedynamic structures of the seemingly complex processes, such as river flow variations, might be betterunderstood using nonlinear deterministic chaotic models than the stochastic ones. In this paper,...
متن کاملDetecting Huntington Patient Using Chaotic Features of Gait Time Series
Huntington's disease (HD) is a congenital, progressive, neurodegenerative disorder characterized by cognitive, motor, and psychological disorders. Clinical diagnosis of HD relies on the manifestation of movement abnormalities. In this study, we introduce a mathematical method for HD detection using step spacing. We used 16 walking signals as control and 20 walking signals as HD. We took a s...
متن کاملChaotic dynamic analysis and nonlinear control of blood glucose regulation system in type 1 diabetic patients
In this paper, chaotic dynamic and nonlinear control in a glucose-insulin system in types I diabetic patients and a healthy person have been investigated. Chaotic analysis methods of the blood glucose system include Lyapunov exponent and power spectral density based on the time series derived from the clinical data. Wolf's algorithm is used to calculate the Lyapunov exponent, which positive val...
متن کاملA Novel Fuzzy Based Method for Heart Rate Variability Prediction
Abstract In this paper, a novel technique based on fuzzy method is presented for chaotic nonlinear time series prediction. Fuzzy approach with the gradient learning algorithm and methods constitutes the main components of this method. This learning process in this method is similar to conventional gradient descent learning process, except that the input patterns and parameters are stored in mem...
متن کامل