2022
DOI: 10.3390/sym14010115
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Fast Computation of Highly Oscillatory ODE Problems: Applications in High-Frequency Communication Circuits

Abstract: The paper demonstrates symmetric integral operator and interpolation based numerical approximations for linear and nonlinear ordinary differential equations (ODEs) with oscillatory factor x′=ψ(x)+χω(t), where the function χω(t) is an oscillatory forcing term. These equations appear in a variety of computational problems occurring in Fourier analysis, computational harmonic analysis, fluid dynamics, electromagnetics, and quantum mechanics. Classical methods such as Runge–Kutta methods etc. fail to approximate t… Show more

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Cited by 15 publications
(8 citation statements)
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“…Optimal water application or control was achieved using a convolution neural network (CNN) for a sugarcane crop. The proposed CNN provided better water control with high accuracy compared to other models [67][68][69][70]. Although several factors help in attaining irrigation optimization, evapotranspiration is the most preferred as it is derived using other key parameters.…”
Section: Artificial Neural Network and Machine Learning For Irrigationmentioning
confidence: 98%
“…Optimal water application or control was achieved using a convolution neural network (CNN) for a sugarcane crop. The proposed CNN provided better water control with high accuracy compared to other models [67][68][69][70]. Although several factors help in attaining irrigation optimization, evapotranspiration is the most preferred as it is derived using other key parameters.…”
Section: Artificial Neural Network and Machine Learning For Irrigationmentioning
confidence: 98%
“…These algorithms are commonly used in Machine learning to deliver precise outcomes for a wide range of classification and prediction issues [ 49 ]. Below commonly used ML algorithms defined.…”
Section: Background and Related Workmentioning
confidence: 99%
“…In Figure 10 a,b, we compare the Hungarian-based content delivery scheme with the random content delivery scheme [ 48 , 49 , 50 , 51 , 52 , 53 ] for minimizing the overall content delay and the power consumption of the system, respectively. We show that the Hungarian-based delivery scheme works much better as compared to random content delivery.…”
Section: Performance Evaluationmentioning
confidence: 99%
“…Hence, by adjusting the values of the two weight coeffici 𝜉 and 𝜚, the performance of the system can be improved. In Figure 10a,b, we compare the Hungarian-based content delivery scheme wit random content delivery scheme [48][49][50][51][52][53] for minimizing the overall content delay an power consumption of the system, respectively. We show that the Hungarian-based livery scheme works much better as compared to random content delivery.…”
Section: Performance Comparison For the Content Delay And Power Consu...mentioning
confidence: 99%