Publication:
Saddlepoint Approximation of the Error Probability of Binary Hypothesis Testing

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URI: https://hdl.handle.net/10016/27525
ISSN: 2157-8117
ISBN: 978-1-5386-4780-6
UXXI: CC/0000027956
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saddlepoint_ISIT_2018_ps.pdf (288.82 KB)
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2018-08-16
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IEEE
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Abstract
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between two i.i.d. distributions. The approximation is accurate, simple to compute, and yields a unified analysis in different asymptotic regimes. The proposed formulation is used to efficiently compute the meta-converse lower bound for moderate block-lengths in several cases of interest.
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Error probability, Testing, Random variables, AWGN channels, Laplace equations, Gaussian distribution
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IEEE International Symposium on Information Theory (ISIT 2018), 17-22 June 2018, Vail, Colorado, USA. [Proceedings], 5 p.
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