Recently, robust adaptive filtering approaches relied on the Maximum Versoria Criterion (MVC) have gained the attention of researchers and have been widely studied. In this brief, with the energy conservation approach...
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Recently, robust adaptive filtering approaches relied on the Maximum Versoria Criterion (MVC) have gained the attention of researchers and have been widely studied. In this brief, with the energy conservation approach, transient and steady-state mean-square deviation (MSD) analysis of the standard constrained MVC (CMVC) are derived under both Gaussian and non-Gaussian noise distributions. For a Gaussian noise condition, an accurate solution is obtained, while for non-Gaussian noise conditions, we used approximate Taylor's expansion to derive the transient and steady-state MSD. Finally, we evaluated the theoretical analysis with some numerical simulations of system identification in different Gaussian and non-Gaussian noise scenarios to validate the finding.
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