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- W2154690632 abstract "Linear processes are suitable for modeling random received waveforms in a scattering medium, which represents radar, sonar and multipath communication channels. We address a continuous-time detection problem where both the noise (hypothesis H/sub 0/) and signal-plus-noise (H/sub 1/) waveforms are modeled as linear processes. Uncertainty in the nominal model is considered in the form of classes of probability distributions induced on a function space by the processes under the two hypotheses. By embedding the linear processes in the larger clam of infinitely divisible processes and using an integral representation for the latter class, we identify the pair of distributions that are least favorable for the discrimination of linear processes; an optimal detector designed for these distributions is robust for the uncertainty classes considered." @default.
- W2154690632 created "2016-06-24" @default.
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- W2154690632 date "2005-08-24" @default.
- W2154690632 modified "2023-09-27" @default.
- W2154690632 title "Robust Continuous-Time Detection of Linear Processes" @default.
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- W2154690632 doi "https://doi.org/10.1109/isit.1993.748332" @default.
- W2154690632 hasPublicationYear "2005" @default.
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