Advances in Concurrent Computing for Digital Stochastic Measurement Simulation

Author:

Pjevalica Nebojsa1ORCID,Pjevalica Velibor2,Petrovic Nenad3

Affiliation:

1. Faculty of Technical Sciences, Computing and Control Engineering Department, University of Novi Sad, Trg D. Obradovića 6, 21000 Novi Sad, Serbia

2. JP Srbijagas, Technical Provision Section, Narodnog Fronta 12, Novi Sad, Serbia

3. School of Electrical Engineering Stari Grad, Visokog Stevana 37, 11000 Belgrade, Serbia

Abstract

This paper introduces a concurrent computing technique for the acceleration of digital stochastic measurement simulations. The digital stochastic measurement presents an advanced methodology based on the specific parallel hardware structure, utilized for an orthogonal transformation calculus/decomposition. Methodology is analyzed in detail, starting from the very basic idea, toward recent references, covering main research directions and trends. An oversampling nature of the evaluated digital stochastic measurement, along with demanding arithmetic requirements, implies exhausting simulation complexity. As a test case, several typical power grid signals were harmonically analyzed through a discrete Fourier transformation based on the proposed methodology. A harmonic decomposition was simulated with several levels of computing concurrency. Through all the simulated scenarios main success criterion was model accuracy, while the parameter used for selection of the optimal simulation computing technique was the overall calculus speed. Final results exposed thread pool computing technique as an optimal simulation platform.

Funder

Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja

Publisher

World Scientific Pub Co Pte Lt

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Electrical and Electronic Engineering,Hardware and Architecture

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Stochastic Smart Grid Meter for Industry 4.0—From an Idea to the Practical Prototype;Springer Proceedings in Mathematics & Statistics;2022

2. Calibration of EOG and ECG instrumentation modules in smart biofeedback system;2020 International Conference Mechatronic Systems and Materials (MSM);2020-07

3. Stochastic approach for controllable measurement uncertainty in Industry 4.0 applications;2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT;2020-06

4. Measurement of Event-Related Brain Potentials (ERP) Amplitude and Latency Based on Digital Stochastic Measurement over Interval;Elektronika ir Elektrotechnika;2020-04-25

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