Experimentally approved generalized model for circuit applications

Abstract

Summary In this paper, generalized model based on the multiplicative least square method presented and showed that it is convenient to approximate observation in the electrical system analysis. The introduced model is exponential based and relies on parametric values. The advantage of the method is due to exponential derivation process within multiplicative calculus and has the flexibility to represent widely used functions such as Gaussian and exponentials. In spite of numerous results on the best fitting model, we study the robustness of the method by making direct comparisons with Matlab built‐in functions. The presented model is challenging because modern electrical circuits and systems are faced with different types of inputs that require near exact representation for accurate processing. Some real applications of exponential‐based data were selected to demonstrate the applicability and efficiency of the proposed representation.

Predicting the spread of COVID-19 with a machine learning technique and multiplicative calculus

“…Therefore, we propose to use a general model with the exponential functions ( 7 – 9 ) Equation ( 10 ) is introduced in the paper Bilgehan et al. ( 2018 ). As the function ( 10 ) approaches to Gaussian function.…”

“…Additionally, the MBM in ( 10 ) used effectively in the paper Bilgehan et al. ( 2018 ) to introduce accurate solution to modern electrical circuits and systems.…”

“…In the literature, it was seen that the MLSM was, respectively, applied to the exponential signal processing Ozyapici and Bilgehan ( 2016 ), the low noise measurement in electrical circuits Bilgehan et al. ( 2018 ) and the experimental data in electrical circuits and systems Ozyapici and Bilgehan ( 2016 ). The general formula of MLSM can be introduced as follows: In many applications as well as the spread of coronavirus, the set of real data depends on observation.…”

Generalized probability density function and applications to the experimental data in electrical circuits and systems

“…After other studies, 1,14,15 the authors encourage to define a generalized probability density to fit the randomly varying data in the electrical systems. This superiority of the multiplicative calculi depends on exponential functions.…”

“…In Bilgehan et al, 14 the extended model is introduced and applied successfully in an electrical circuit. The function (1) spans the well‐known exponential, Gaussian, and Rayleigh functions given respectively as where a > 0.…”