Perturbation Approach to Polynomial Root Estimation and Expected Maximum Modulus of Zeros with Uniform Perturbations

This paper presents a significant extension of perturbation theory techniques for estimating the roots of polynomials. Building upon foundational results and recent work by Pakdemirli and Yurtsever, as well as taking inspiration from the concept of probabilistic bounds introduced by Sheikh et al., we develop and prove several novel theorems that address a wide range of polynomial structures. These include polynomials with multiple large coefficients, coefficients of different orders, alternating coefficient orders, large linear and constant terms, and exponentially decreasing coefficients. Among the key contributions is a theorem that establishes an upper bound on the expected maximum modulus of the zeros of polynomials with uniformly distributed perturbations in their coefficients. The theorem considers the case where all but the leading coefficient receive a uniformly and independently distributed perturbation in the interval [−1,1]. Our approach provides a comprehensive framework for estimating the order of magnitude of polynomial roots based on the structure and magnitude of their coefficients without the need for explicit root-finding algorithms. The results offer valuable insights into the relationship between coefficient patterns and root behavior, extending the applicability of perturbation-based root estimation to a broader class of polynomials. This work has potential applications in various fields, including random polynomials, control systems design, signal processing, and numerical analysis, where quick and reliable estimation of polynomial roots is crucial. Our findings contribute to the theoretical understanding of polynomial properties and provide practical tools for engineers and scientists dealing with polynomial equations in diverse contexts.

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Publication Details

Journal
Mathematics
Published
2024-09-26
DOI
https://doi.org/10.3390/math12192993
Citations
1
Primary Topic
Random Matrices and Applications
Type
article
Field-Weighted Citation Impact
0.71
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article

Perturbation Approach to Polynomial Root Estimation and Expected Maximum Modulus of Zeros with Uniform Perturbations

Mohammed M. A. Almazah, Ibrahim Nafisah, Javid Gani Dar, Badr S. Alnssyan et al.
1 citations
Mathematics
Random Matrices and Applications
0.71
article

Perturbation Approach to Polynomial Root Estimation and Expected Maximum Modulus of Zeros with Uniform Perturbations

Mohammed M. A. Almazah, Ibrahim Nafisah, Javid Gani Dar, Badr S. Alnssyan, Mohammed A. Alshahrani, Sajad Ahmad Sheikh
article en
1 citations

Abstract

This paper presents a significant extension of perturbation theory techniques for estimating the roots of polynomials. Building upon foundational results and recent work by Pakdemirli and Yurtsever, as well as taking inspiration from the concept of probabilistic bounds introduced by Sheikh et al., we develop and prove several novel theorems that address a wide range of polynomial structures. These include polynomials with multiple large coefficients, coefficients of different orders, alternating coefficient orders, large linear and constant terms, and exponentially decreasing coefficients. Among the key contributions is a theorem that establishes an upper bound on the expected maximum modulus of the zeros of polynomials with uniformly distributed perturbations in their coefficients. The theorem considers the case where all but the leading coefficient receive a uniformly and independently distributed perturbation in the interval [−1,1]. Our approach provides a comprehensive framework for estimating the order of magnitude of polynomial roots based on the structure and magnitude of their coefficients without the need for explicit root-finding algorithms. The results offer valuable insights into the relationship between coefficient patterns and root behavior, extending the applicability of perturbation-based root estimation to a broader class of polynomials. This work has potential applications in various fields, including random polynomials, control systems design, signal processing, and numerical analysis, where quick and reliable estimation of polynomial roots is crucial. Our findings contribute to the theoretical understanding of polynomial properties and provide practical tools for engineers and scientists dealing with polynomial equations in diverse contexts.

MathematicsVol. 12(19)
University of Kashmir (IN), Prince Sattam Bin Abdulaziz University (SA), Qassim University (SA), Symbiosis International University (IN), King Saud University (SA), King Khalid University (SA)
Openalex Percentile: Top 26%
Random Matrices and Applications
0.71
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