Calculation of Electric Circuits Using the Fast Kirchhoff Method

Ďuriš, Viliam; Chertanovskiy, Aleksey G.; Chumarov, Sergey G.; Kartuzov, Aleksandеr V.

doi:10.18421/tem111-09

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…Herein, based on RECM, we propose a new model, RGM, that can generate possible routes for people when given specific origins and destinations. Based on the physical architecture of the electric circuit, the flow pattern of human current from the origin to the destination can be obtained by solving Kirchhoff's law 36 under the condition that electrodes are placed at the origin and destination points.…”

Section: Resultsmentioning

confidence: 99%

Human mobility description by physical analogy of electric circuit network based on GPS data

Zhong,

Takayasu,

Takayasu

2024

Sci Rep

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Human mobility in an urban area is complicated; the origins, destinations, and transportation modes of each person differ. The quantitative description of urban human mobility has recently attracted the attention of researchers, and it highly related to urban science problems. Herein, combined with physics inspiration, we introduce a revised electric circuit model (RECM) in which moving people are regarded as charged particles and analogical concepts of electromagnetism such as human conductivity and human potential enable us to capture the characteristics of urban human mobility. We introduce the unit system, ensure the uniqueness of the calculation result, and reduce the computation cost of the algorithm to 1/10,000 compared with the original ECM, making the model more universal and easier to use. We compared features including human conductivity and potential between different major cities in Japan to show our improvement of the universality and the application range of the model. Furthermore, based on inspiration of physics, we propose a route generation model (RGM) to simulate a human flow pattern that automatically determines suitable routes between a given origin and destination as a source and sink, respectively. These discoveries are expected to lead to new approaches to the solution of urban science problems.

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Section: Resultsmentioning

confidence: 99%

Human mobility description by physical analogy of electric circuit network based on GPS data

Zhong,

Takayasu,

Takayasu

2024

Sci Rep

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“…The Pearson correlation coefficient of the original signal with the reconstructed signal for sampling 1024 samples is at least 0.999. The profiling of the program shows that the time of the wavelet transformation using FFT is 15,000 times less than with direct numerical integration for sampling a signal of 32,768 samples [11], [15].…”

Section: Discussionmentioning

confidence: 99%

“…The authors have developed ways to increase the speed of MSA in the frequency domain based on wavelets constructed in the frequency domain [9]. The authors proposed an MSA algorithm using wavelets based on derivatives of the Gauss function [10], [11]. The proposed algorithm enables reconstructing the image.…”

Section: Introductionmentioning

confidence: 99%

Application of Discrete and Fast Fourier Transforms to Increase the Speed of Multiscale Image Analysis

Ďuriš,

Semenov,

Chumarov

2024

TEM Journal

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The paper compares the accuracy of reconstruction using different wavelets, and the authors also use fast and discrete Fourier transforms together to calculate the forward and inverse continuous wavelet transform in the frequency domain. Due to the use of calculations in the frequency domain, it becomes possible to perform decomposition, reconstruction, image filtering, and other transformations with high performance and precision. For multiscale signal analysis, a wavelet with a rectangular amplitude-frequency response has been constructed, which allows for an increase in the accuracy of decomposition and reconstruction compared to the Mallat algorithm presented in Matlab computer mathematics. At the same time, the time of multiscale analysis is reduced several times compared to the Mallat algorithm.

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“…Gaussian, Poisson, Markov, and hidden Markov processes are all examples of these kinds of statistical models (7) . The statistical models are based on the idea that the signal can be well described as a parametric random process and that the random process's parameters can be found precisely and well-defined (8) . The Markov chain model can be used to study systems with randomness.…”

Section: Introductionmentioning

confidence: 99%

Markov Chain: A Novel Tool for Electronic Ripple Analysis

Vijesh¹,

Kumar²,

Swapna³

et al. 2022

IJST

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Objective: To delineate a novel surrogate approach to analyse the ripple component by constructing a complex network using the Markov model. Methods: Adjacency matrices (A) are constructed from the digital storage oscilloscope output signal of the Full-Wave (FWR) and Half-Wave Rectifiers (HWR) without and with a filter. The centrality measures -indegree, outdegree, in closeness, out closeness, Weighted Network Clustering Coefficient (WNCC) -are also computed for the Markov chain. Findings: With the increase of filter capacitance, more elements in the adjacency matrix become zero. Finally, only one matrix element corresponding to A 10,10 remains nonzero for FWR and A 20,20 for HWR, indicating the total rectification of the signal at 10 volts. The Markov chain analysis shows that as the ripple component decreases, the number of unconnected nodes increases and the self-loop of the last node increases. For the rectifier output without filtering, it is found that all the nodes are interconnected through edges. The greater the filtering efficiency, the greater the indegree and outdegree, and the lesser the incloseness, outcloseness and WNCC measures.

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Calculation of Electric Circuits Using the Fast Kirchhoff Method

Cited by 3 publications

References 13 publications

Human mobility description by physical analogy of electric circuit network based on GPS data

Human mobility description by physical analogy of electric circuit network based on GPS data

Application of Discrete and Fast Fourier Transforms to Increase the Speed of Multiscale Image Analysis

Markov Chain: A Novel Tool for Electronic Ripple Analysis

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