Abstract
In this paper we consider a new way to calculate the logarithm of the Likelihood Ratio Function for Gaussian signals. This approach is based on the standard Kalman filter. Its efficiency is substantiated theoretically, and numerical examples show how such a method works in practice.
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This work was supported in part by the Russian Ministry of Education (grant No. T02-03.2-3427).
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Kulikova, M.V. (2003). On Effective Computation of the Logarithm of the Likelihood Ratio Function for Gaussian Signals. In: Sloot, P.M.A., Abramson, D., Bogdanov, A.V., Gorbachev, Y.E., Dongarra, J.J., Zomaya, A.Y. (eds) Computational Science — ICCS 2003. ICCS 2003. Lecture Notes in Computer Science, vol 2658. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44862-4_45
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DOI: https://doi.org/10.1007/3-540-44862-4_45
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