<div class="csl-bib-body">
<div class="csl-entry">Xaver, F., Gerstoft, P., Matz, G., & Mecklenbräuker, C. (2013). Analytic Sequential Weiss-Weinstein Bounds. <i>IEEE Transactions on Signal Processing</i>, <i>61</i>(20), 5049–5062. https://doi.org/10.1109/tsp.2013.2273886</div>
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dc.identifier.issn
1053-587X
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/155084
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dc.description.abstract
In this paper, we explore a sequential Bayesian bound for state-space models focusing on hybrid continuous and discrete random states. We provide an analytic recursion for the sequential Weiss-Weinstein (SWW) bound for linear state-space models with solutions for Gaussian, uniform, and exponential distributions as derived, as well as for a combination of these. We compare the SWW bound for discretized states with the corresponding bound for the continuous states. The SWW bound is contrasted with the sequential Cramér-Rao bound for Gaussian distributions. Practical issues of SWW bounds are discussed and numerical simulation results provide insights into their behavior.
