QML blind deconvolution: Asymptotic analysis LNCS Bronstein, Alexander ; https://orcid.org/0000-0001-9699-8730 Bronstein, Michael M. Zibulevsky, Michael Zeevi, Yehoshua Y. Blind deconvolution is considered as a problem of quasi maximum likelihood (QML) estimation of the restoration kernel. Simple closed-form expressions for the asymptotic estimation error are derived. The asymptotic performance bounds coincide with the Cramér-Rao bounds, when the true ML estimator is used. Conditions for asymptotic stability of the QML estimator are derived. Special cases when the estimator is super-efficient are discussed. Springer Nature 2004 info:eu-repo/semantics/conferenceObject doc-type:conferenceObject text http://purl.org/coar/resource_type/c_5794 https://research-explorer.ista.ac.at/record/18335 Bronstein AM, Bronstein MM, Zibulevsky M, Zeevi YY. QML blind deconvolution: Asymptotic analysis. In: <i>Proceedings of the 5th International Conference on Independent Component Analysis and Blind Signal Separation</i>. Vol 3195. Springer Nature; 2004:677–684. doi:<a href="https://doi.org/10.1007/978-3-540-30110-3_86">10.1007/978-3-540-30110-3_86</a> eng info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-540-30110-3_86 info:eu-repo/semantics/altIdentifier/issn/0302-9743 info:eu-repo/semantics/altIdentifier/issn/1611-3349 info:eu-repo/semantics/altIdentifier/isbn/9783540230564 info:eu-repo/semantics/altIdentifier/isbn/9783540301103 info:eu-repo/semantics/closedAccess