Binary Classification of Fractal Time Series by Machine Learning Methods

Kirichenko, Lyudmyla; Радівілова, Тамара; Bulakh, Vitalii

doi:10.1007/978-3-030-26474-1_49

Cited by 23 publications

(4 citation statements)

References 25 publications

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“…12B). Features based on RQA measures are meanwhile frequently used for classification purposes using SVMs, CNNs, k -nearest neighbour or random forest classifications [118][119][120][121][122][123][124] and the ML-toolbox offers a variety of other methods for clustering and feature classification (Fig. 12B).…”

Section: Recurrence and Machine Learningmentioning

confidence: 99%

Trends in recurrence analysis of dynamical systems

Marwan

Kraemer

2023

Eur. Phys. J. Spec. Top.

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The last decade has witnessed a number of important and exciting developments that had been achieved for improving recurrence plot-based data analysis and to widen its application potential. We will give a brief overview about important and innovative developments, such as computational improvements, alternative recurrence definitions (event-like, multiscale, heterogeneous, and spatio-temporal recurrences) and ideas for parameter selection, theoretical considerations of recurrence quantification measures, new recurrence quantifiers (e.g. for transition detection and causality detection), and correction schemes. New perspectives have recently been opened by combining recurrence plots with machine learning. We finally show open questions and perspectives for futures directions of methodical research.

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Section: Recurrence and Machine Learningmentioning

confidence: 99%

Trends in recurrence analysis of dynamical systems

Marwan

Kraemer

2023

Eur. Phys. J. Spec. Top.

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“…The field of Fig. 12 The calculated spectrum of Lyapunov exponents for the studied system application of these devices is extremely wide: here we can refer to the Internet of things, automotive systems, sensor networks, monitoring systems for sick patients, distributed control systems, cyber-physics industrial systems, networks guided by artificial intelligence [20,32]. The algorithms for encrypting information forming the technology of light cryptography are intended for use in devices with limited memory resources and processor time.…”

Section: Determination Of the Period Of Pseudorandom Sequences For Crmentioning

confidence: 99%

Approaches to Building a Chaotic Communication System

Kushnir

Vovchuk

Haliuk

et al. 2020

Data-Centric Business and Applications

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Nowadays are being held intensive researches involving the use of deterministic chaos in communication systems. Indeed chaotic oscillations in such systems serve as a carrier of information signals, and means of encryption, both in hardware and in software. This work is devoted to the complex analysis of the practical implementation of a chaotic secure communication system. The generalized synchronization as a synchronization response was selected. The circuit implementation of a modified Colpitts oscillator as a source of chaos was proposed. We also discussed questions of modeling chaotic oscillations and, in this context, analyzing the differences between chaotic, pseudo-chaotic and pseudo-random oscillations.

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“…Modern studies of the processes occurring in technical systems have revealed their self-similar nature. So in works [7][8][9][10] a study of self-similar processes is carried out, both of signals of various nature and the properties of traffic in networks.…”

Section: Learning Ann As a Special Case Of The Formation Of Virtual Images Of Signal For The Unification Of Procedures For Processing Radmentioning

confidence: 99%

Adaptive Semantic Analysis of Radar Data Using Fuzzy Transform

Solonska

Zhyrnov

2020

Data-Centric Business and Applications

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The development of a new adaptive system of radar data semantic analysis with their non-stationarity, which is based on both numerical and logical methods of multiscanning processing of signals and methods of artificial intelligence using fuzzy transformations of the universe of signals and signal images, is proposed. The possibility of its hardware and software implementation is considered. The results of computer modeling, theoretical and experimental researches with processing of real radar signals are presented. The elements of logical analysis and algebra of finite predicates (AFP) are selected as mathematical apparatus. As experimental studies show, AFP is an appropriate tool for logical-mathematical constructions, with which it's possible to describe the radar operator actions. The basic concepts of Boolean algebra and graph theory are also used. The practical value of the work is: a method for formalizing the processes of perception and transformation of signals and signal images, algorithms and software are intended for information radar systems with natural-language intellectual interface; also for support the design of information structures. Mathematical and software results can be used in the systems of automatic processing of radar information, particularly, in the intelligent radar and radio-electronic systems and complexes for monitoring of mobile air and ground objects.

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Binary Classification of Fractal Time Series by Machine Learning Methods

Cited by 23 publications

References 25 publications

Trends in recurrence analysis of dynamical systems

Trends in recurrence analysis of dynamical systems

Approaches to Building a Chaotic Communication System

Adaptive Semantic Analysis of Radar Data Using Fuzzy Transform

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