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Quadratic Estimation of Multivariate Signals from Randomly Delayed Measurements*

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Abstract

This paper discusses the least-squares quadratic estimation problem of a multivariate discrete signal, from noisy measurements which can be delayed by one sampling period. The delay in the observations is assumed to be random and the probability of a delay in each measurement is known. The quadratic recursive estimation algorithm, which uses only the delay probabilities and the moments (up to fourth-order) of the signal and noise-measurement, is derived from a linear estimation algorithm for a suitably defined augmented system.

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Correspondence to S. Nakamori.

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*This work was partially supported by the ‘Ministerio de Ciencia y Tecnología’ under contract BFM2002-00932.

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Nakamori, S., Hermoso-Carazo, A. & Linares-Pérez, J. Quadratic Estimation of Multivariate Signals from Randomly Delayed Measurements*. Multidim Syst Sign Process 16, 417–438 (2005). https://doi.org/10.1007/s11045-005-4127-2

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  • DOI: https://doi.org/10.1007/s11045-005-4127-2

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