Abstract:
Within this paper, the auto-compensated electrostatic induction probe is characterized by generating its Point Spread Function (PSF) and its inverse. New approaches based...Show MoreMetadata
Abstract:
Within this paper, the auto-compensated electrostatic induction probe is characterized by generating its Point Spread Function (PSF) and its inverse. New approaches based on the stochastic Search Algorithms (SSA) are proposed to obtain several Point Spread Functions and their inverses. Radial Basis Functions Neural Networks are used to approximate the original measures in order to have two-dimensional array representation of the potential on the surface of the material. These new approaches are tested, validated, and compared to each other in term of rapid convergence and best cost obtained. The obtained PSFs and inverse PSFs give approximations within a good accuracy in predicting the measure or the real distribution of the potential on the surface of the material.
Date of Conference: 06-10 May 2022
Date Added to IEEE Xplore: 28 November 2022
ISBN Information: