Acceleration of time series entropy algorithms

Tomčala, Jiří

doi:10.1007/s11227-018-2657-2

Cited by 11 publications

(11 citation statements)

References 10 publications

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“…To accomplish this, a model of three degrees of freedom was built and then simulated in MATLAB [23] using the Runge-Kutta method as an in-function ode45 adaptive solver, and a final evaluation was performed in R [20] applying the Chaos01 [21] and TSEntropies [22] packages.…”

Section: Discussionmentioning

confidence: 99%

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Motion of an Unbalanced Impact Body Colliding with a Moving Belt

Lampart

Zapoměl

2021

Mathematics

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In the field of mechanical engineering, conveyors and moving belts are frequently used machine parts. In many working regimes, they are subjected to sudden loading, which can be a source of irregular motion in the impacting bodies and undesirable behavior in the working machine. This paper deals with a mechanical model where colisions between an impact body and a moving belt take place. The impact body is constrained by a flexible rope, the upper end of which is excited by a slider in the vertical direction. The behavior of the system was investigated in terms of its dependence on the amplitude and frequency of excitation given by the movement of the slider, and the eccentricity of the center of gravity of the impact body. Outputs of the computations indicate that different combinations of the analyzed parameters lead to high complexity of the system’s movement. The bifurcation analysis shows multiple periodic areas changed by chaotic regions. The research carried out provides more details about the behavior and properties of strongly nonlinear mechanical systems resulting from impacts and dry friction. The obtained information will enable designers to propose parameters for industrial machines that make it possible to avoid their working at undesirable operating levels.

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Section: Discussionmentioning

confidence: 99%

“…The evaluation of the movement character was performed in the free software environment R [20] using the packages Chaos01 [21] and TSEntropies [22]. This dynamics mining process was applied on simulation outputs that were obtained by the Runge-Kutta method of the fourth order using MATLAB [23] (solver ode45).…”

Section: Three Parameters' Dynamics Depictionmentioning

confidence: 99%

Motion of an Unbalanced Impact Body Colliding with a Moving Belt

Lampart

Zapoměl

2021

Mathematics

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“…As can be seen from this image, the values of the new accelerated algorithms are at different levels than their original versions. This fact is discussed in detail in [ 6 ], where it is also shown that their ability to detect an increase or decrease in complexity of the time series is roughly the same as in their original versions. A more detailed analysis of this phenomenon goes beyond the scope of this article.…”

Section: Supercomputer Power Consumption Time Seriesmentioning

confidence: 98%

“…Quadratic time complexity of the Approximate and Sample Entropy algorithms was the main reason why their accelerated modifications Fast Approximate Entropy and Fast Sample Entropy have been proposed in [ 6 ]. The original Approximate Entropy algorithm looks for mutually similar sub-sequences by comparing all possible sub-sequences with each other.…”

Section: New Fast Algorithmsmentioning

confidence: 99%

“…From the point of view of the focus of this paper, the most important are calculations of ApEn, SampEn, FastApEn, and FastSampEn values of the supercomputer power consumption time series powerTS from the real world and therefore the attention will be given especially on them. The detailed results of calculations of artificially created time series as sinTS and rnormTS have already been published in [ 6 ].…”

Section: Benchmarks and Comparisonmentioning

confidence: 99%

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New Fast ApEn and SampEn Entropy Algorithms Implementation and Their Application to Supercomputer Power Consumption

Tomčala

2020

Entropy

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Approximate Entropy and especially Sample Entropy are recently frequently used algorithms for calculating the measure of complexity of a time series. A lesser known fact is that there are also accelerated modifications of these two algorithms, namely Fast Approximate Entropy and Fast Sample Entropy. All these algorithms are effectively implemented in the R software package TSEntropies. This paper contains not only an explanation of all these algorithms, but also the principle of their acceleration. Furthermore, the paper contains a description of the functions of this software package and their parameters, as well as simple examples of using this software package to calculate these measures of complexity of an artificial time series and the time series of a complex real-world system represented by the course of supercomputer infrastructure power consumption. These time series were also used to test the speed of this package and to compare its speed with another R package pracma. The results show that TSEntropies is up to 100 times faster than pracma and another important result is that the computational times of the new Fast Approximate Entropy and Fast Sample Entropy algorithms are up to 500 times lower than the computational times of their original versions. At the very end of this paper, the possible use of this software package TSEntropies is proposed.

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Movement Characteristics of a Model with Circular Equilibrium

Lampart

Nagyová

2020

Chaos and Complex Systems

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Acceleration of time series entropy algorithms

Cited by 11 publications

References 10 publications

Motion of an Unbalanced Impact Body Colliding with a Moving Belt

Motion of an Unbalanced Impact Body Colliding with a Moving Belt

New Fast ApEn and SampEn Entropy Algorithms Implementation and Their Application to Supercomputer Power Consumption

Movement Characteristics of a Model with Circular Equilibrium

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