Abstract
Recently Rao et al. [13] established the strong consistency and asymptotic normality of the maximum likelihood estimates of the 2-D superimposed exponential signal model under the assumption of normality of the error random variables. In this paper we investigate the theoretical properties of the least squares estimates of the same model under the assumption of general error distribution. The strong consistency and asymptotic distribution of the least squares estimates have been obtained. Further extension to the multidimensional case has been proposed.
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The work is partly supported by a Grant (No: SR/OY/M-06/93) of the Department of Science and Technology, Government of India
The work is partly supported by the National Board of Higher Mathematics, Department of Atomic Energy, Government of India
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Kundu, D., Mitra, A. Asymptotic properties of the least squares estimates of 2-D exponential signals. Multidim Syst Sign Process 7, 135–150 (1996). https://doi.org/10.1007/BF01827810
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DOI: https://doi.org/10.1007/BF01827810