An orthogonal projection iterative method and its applications

In this study, we explore the iterative processes involving the orthogonal projection of generalized inverses with applications to state estimation, signal processing and truss problems for matrix computations. We investigate the behavior and convergence properties of these iterative methods. A sensitivity analysis of the parameters is performed to examine their influence on the convergence characteristics of iterative methods. We specifically examine the orthogonal projection process by monitoring the trace and Frobenius norm of the deterministic and random matrices, providing information on the convergence characteristics and stability of the methods.

Authors

Publication Details

Journal
Journal of Applied and Numerical Analysis
Published
2025-09-16
DOI
https://doi.org/10.30970/ana.2025.3.53
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An orthogonal projection iterative method and its applications

Hemant Kumar Nashine, Neha Ramesh Girhe
Journal of Applied and Numerical Analysis
Matrix Theory and Algorithms
article

An orthogonal projection iterative method and its applications

Hemant Kumar Nashine, Neha Ramesh Girhe
article en

Abstract

In this study, we explore the iterative processes involving the orthogonal projection of generalized inverses with applications to state estimation, signal processing and truss problems for matrix computations. We investigate the behavior and convergence properties of these iterative methods. A sensitivity analysis of the parameters is performed to examine their influence on the convergence characteristics of iterative methods. We specifically examine the orthogonal projection process by monitoring the trace and Frobenius norm of the deterministic and random matrices, providing information on the convergence characteristics and stability of the methods.

Journal of Applied and Numerical AnalysisVol. 3
Openalex Percentile: Top 74%
Matrix Theory and Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.