This research investigates iterative methods for orthogonal projections in signal processing and matrix computations, highlighting convergence properties.
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.
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Girhe et al. (2025) studied this question.
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