Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A New Smoothing Technique based on the Parallel Concatenation of
  Forward/Backward Bayesian Filters: Turbo Smoothing   Recently, a novel method for developing filtering algorithms, based on the
parallel concatenation of Bayesian filters and called turbo filtering, has been
proposed. In this manuscript we show how the same conceptual approach can be
exploited to devise a new smoothing method, called turbo smoothing. A turbo
smoother combines a turbo filter, employed in its forward pass, with the
parallel concatenation of two backward information filters used in its backward
pass. As a specific application of our general theory, a detailed derivation of
two turbo smoothing algorithms for conditionally linear Gaussian systems is
illustrated. Numerical results for a specific dynamic system evidence that
these algorithms can achieve a better complexity-accuracy tradeoff than other
smoothing techniques recently appeared in the literature.

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The categories of this paper are: quant-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: adap-org
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The categories of this paper are: nucl-th
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The categories of this paper are: comp-gas
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The categories of this paper are: chao-dyn
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The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
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The categories of this paper are: math-ph
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The categories of this paper are: funct-an
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The categories of this paper are: eess
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The categories of this paper are: astro-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: econ
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The categories of this paper are: plasm-ph
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The categories of this paper are: supr-con