FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2091489596> ?p ?o ?g. }

• W2091489596 endingPage "2357" @default.
• W2091489596 startingPage "2345" @default.
• W2091489596 abstract "In this two-part paper, we consider the problem of adaptive multidimensional/multichannel signal detection in Gaussian noise with unknown covariance matrix. The test data (primary data) is assumed as a collection of sample vectors, arranged as the columns of a rectangular data array. The rows and columns of the signal matrix are both assumed to lie in known subspaces, but with unknown coordinates. Due to this feature of the signal structure, we name this kind of signal as the double subspace signal. Part I of this paper focuses on the adaptive detection in homogeneous environments, while Part II deals with the adaptive detection in partially homogeneous environments. Precisely, in this part, we derive the generalized likelihood ratio test (GLRT), Rao test, Wald test, as well as their two-step variations, in homogeneous environments. Three types of spectral norm tests (SNTs) are also introduced. All these detectors are shown to possess the constant false alarm rate (CFAR) property. Moreover, we discuss the differences between them and show how they work. Another contribution is that we investigate various special cases of these detectors. Remarkably, some of them are well-known existing detectors, while some others are still new. At the stage of performance evaluation, conducted by Monte Carlo simulations, both matched and mismatched signals are dealt with. For each case, more than one scenario is considered." @default.
• W2091489596 created "2016-06-24" @default.
• W2091489596 creator A5027835055 @default.
• W2091489596 creator A5040272812 @default.
• W2091489596 creator A5070756898 @default.
• W2091489596 creator A5080756015 @default.
• W2091489596 date "2014-05-01" @default.
• W2091489596 modified "2023-10-18" @default.
• W2091489596 title "Adaptive Double Subspace Signal Detection in Gaussian Background—Part I: Homogeneous Environments" @default.
• W2091489596 cites W1899196398 @default.
• W2091489596 cites W1963758962 @default.
• W2091489596 cites W1973176871 @default.
• W2091489596 cites W1976044906 @default.
• W2091489596 cites W1979315806 @default.
• W2091489596 cites W1986921156 @default.
• W2091489596 cites W1994992001 @default.
• W2091489596 cites W2008662406 @default.
• W2091489596 cites W2017941872 @default.
• W2091489596 cites W2024275106 @default.
• W2091489596 cites W2029415566 @default.
• W2091489596 cites W2030471142 @default.
• W2091489596 cites W2034748641 @default.
• W2091489596 cites W2038407254 @default.
• W2091489596 cites W2039882402 @default.
• W2091489596 cites W2054521533 @default.
• W2091489596 cites W2058683736 @default.
• W2091489596 cites W2063677402 @default.
• W2091489596 cites W2068989375 @default.
• W2091489596 cites W2069205140 @default.
• W2091489596 cites W2069215735 @default.
• W2091489596 cites W2070692801 @default.
• W2091489596 cites W2071878347 @default.
• W2091489596 cites W2075013484 @default.
• W2091489596 cites W2075261934 @default.
• W2091489596 cites W2081936987 @default.
• W2091489596 cites W2083836808 @default.
• W2091489596 cites W2085468243 @default.
• W2091489596 cites W2088265797 @default.
• W2091489596 cites W2092731445 @default.
• W2091489596 cites W2092956745 @default.
• W2091489596 cites W2096972831 @default.
• W2091489596 cites W2098044727 @default.
• W2091489596 cites W2099014959 @default.
• W2091489596 cites W2099040013 @default.
• W2091489596 cites W2102649267 @default.
• W2091489596 cites W2103148898 @default.
• W2091489596 cites W2103565703 @default.
• W2091489596 cites W2106199973 @default.
• W2091489596 cites W2106999806 @default.
• W2091489596 cites W2107470042 @default.
• W2091489596 cites W2113028008 @default.
• W2091489596 cites W2113472897 @default.
• W2091489596 cites W2116345224 @default.
• W2091489596 cites W2118141734 @default.
• W2091489596 cites W2118896231 @default.
• W2091489596 cites W2119291159 @default.
• W2091489596 cites W2121474395 @default.
• W2091489596 cites W2121746155 @default.
• W2091489596 cites W2123200950 @default.
• W2091489596 cites W2123776775 @default.
• W2091489596 cites W2127748925 @default.
• W2091489596 cites W2131480555 @default.
• W2091489596 cites W2134001300 @default.
• W2091489596 cites W2135915867 @default.
• W2091489596 cites W2142517930 @default.
• W2091489596 cites W2144158572 @default.
• W2091489596 cites W2149826217 @default.
• W2091489596 cites W2151166516 @default.
• W2091489596 cites W2152071579 @default.
• W2091489596 cites W2152451050 @default.
• W2091489596 cites W2154051216 @default.
• W2091489596 cites W2156626848 @default.
• W2091489596 cites W2157148515 @default.
• W2091489596 cites W2159376318 @default.
• W2091489596 cites W2165871028 @default.
• W2091489596 cites W2171576754 @default.
• W2091489596 cites W2261039809 @default.
• W2091489596 cites W4242748674 @default.
• W2091489596 cites W4253251748 @default.
• W2091489596 doi "https://doi.org/10.1109/tsp.2014.2309556" @default.
• W2091489596 hasPublicationYear "2014" @default.
• W2091489596 type Work @default.
• W2091489596 sameAs 2091489596 @default.
• W2091489596 citedByCount "140" @default.
• W2091489596 countsByYear W20914895962014 @default.
• W2091489596 countsByYear W20914895962015 @default.
• W2091489596 countsByYear W20914895962016 @default.
• W2091489596 countsByYear W20914895962017 @default.
• W2091489596 countsByYear W20914895962018 @default.
• W2091489596 countsByYear W20914895962019 @default.
• W2091489596 countsByYear W20914895962020 @default.
• W2091489596 countsByYear W20914895962021 @default.
• W2091489596 countsByYear W20914895962022 @default.
• W2091489596 countsByYear W20914895962023 @default.
• W2091489596 crossrefType "journal-article" @default.
• W2091489596 hasAuthorship W2091489596A5027835055 @default.
• W2091489596 hasAuthorship W2091489596A5040272812 @default.
• W2091489596 hasAuthorship W2091489596A5070756898 @default.

• next