Publications by authors named "Vasilios N Katsikis"
A Zeroing Neural Network Approach for Calculating Time-Varying G-Outer Inverse of Arbitrary Matrix.
IEEE Trans Neural Netw Learn Syst
June 2024
Calculation of the time-varying (TV) matrix generalized inverse has grown into an essential tool in many fields, such as computer science, physics, engineering, and mathematics, in order to tackle TV challenges. This work investigates the challenge of finding a TV extension of a subclass of inner inverses on real matrices, known as generalized-outer (G-outer) inverses. More precisely, our goal is to construct TV G-outer inverses (TV-GOIs) by utilizing the zeroing neural network (ZNN) process, which is presently thought to be a state-of-the-art solution to tackling TV matrix challenges.
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- The banking industry's growth has led to an increase in loan applications, but banks have limited assets to lend, making it essential to find safe applicants efficiently.
- A new neural network called the weights and structure determination (WASD) has been developed to enhance the credit and loan approval process by addressing the unique characteristics of each application.
- The WASD algorithm is further improved with a bio-inspired technique called the beetle antennae search (BAS), resulting in better performance and adaptability, supported by a MATLAB package for implementation.
The problem of solving linear equations is considered as one of the fundamental problems commonly encountered in science and engineering. In this article, the complex-valued time-varying linear matrix equation (CVTV-LME) problem is investigated. Then, by employing a complex-valued, time-varying QR (CVTVQR) decomposition, the zeroing neural network (ZNN) method, equivalent transformations, Kronecker product, and vectorization techniques, we propose and study a CVTVQR decomposition-based linear matrix equation (CVTVQR-LME) model.
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