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• W2892008534 abstract "In this paper, we propose a new algorithm for a recursive implementation of constrained multiple model (MM) maximum a posteriori (MAP) estimation. The recursive procedure is formulated in a sliding window fashion, where the measurements are processed sequentially. For each recursion, an iterative alternating coordinate-ascent (ACA) maximization process and our previously developed constrained sequential list Viterbi algorithm (CSLVA) are used to find the best constrained solution (mode and state sequence estimates) within the window. Performance results from simulation of two application examples are provided to demonstrate the capabilities of the proposed method." @default.
• W2892008534 created "2018-09-27" @default.
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• W2892008534 date "2018-07-01" @default.
• W2892008534 modified "2023-10-18" @default.
• W2892008534 title "Recursive Sliding-Window Algorithm for Constrained Multiple-Model MAP Estimation" @default.
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• W2892008534 doi "https://doi.org/10.23919/icif.2018.8455611" @default.
• W2892008534 hasPublicationYear "2018" @default.
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