The Annals of Statistics
- Ann. Statist.
- Volume 24, Number 5 (1996), 1964-1981.
Blind deconvolution of discrete linear systems
We study the blind deconvolution problem in the case where the input noise has a finite discrete support and the transfer linear system is not necessarily minimum phase. We propose a new family of estimators built using algebraic considerations. The estimates are consistent under very wide assumptions: The input signal need not be independently distributed; the cardinality of the finite support may be estimated simultaneously. We consider in particular AR systems: In this case, we prove that the estimator of the parameters is perfect a.s. with a finite number of observations.
Ann. Statist. Volume 24, Number 5 (1996), 1964-1981.
First available in Project Euclid: 20 November 2003
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Gamboa, F.; Gassiat, E. Blind deconvolution of discrete linear systems. Ann. Statist. 24 (1996), no. 5, 1964--1981. doi:10.1214/aos/1069362305. https://projecteuclid.org/euclid.aos/1069362305