{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T10:17:07Z","timestamp":1762251427774},"reference-count":15,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2008,9,12]],"date-time":"2008-09-12T00:00:00Z","timestamp":1221177600000},"content-version":"vor","delay-in-days":6099,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Trans Emerging Tel Tech"],"published-print":{"date-parts":[[1992,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The paper deals with the detection of a known signal embedded in cyclostationary white generalized Gaussian noise. Two cases are considered: the former assumes unknown (but nonrandom) the periodic noise intensity, the latter considers unknown also the noise\u2010shape parameter. Since for these detection problems non uniformly most powerful test exists, the generalized log\u2010likelihood ratio test (GLLRT) is considered because of its asymptotic optimality properties. The GLLRT\u2010based detectors for both cases are synthesized and their asymptotic (i.e., for large sample size) performances are analytically evaluated. Moreover, for finite sample size, the performances, carried out via computer Monte Carlo simulations, are compared with that of the optimum detector, whose synthesis is based on a complete noise characterization.<\/jats:p>","DOI":"10.1002\/ett.4460030107","type":"journal-article","created":{"date-parts":[[2008,9,12]],"date-time":"2008-09-12T12:43:40Z","timestamp":1221223420000},"page":"39-43","source":"Crossref","is-referenced-by-count":4,"title":["Signal detection in cyclostationary generalized gaussian noise with unknown parameters"],"prefix":"10.1002","volume":"3","author":[{"given":"Antonio","family":"Napolitano","sequence":"first","affiliation":[]},{"given":"Luigi","family":"Paura","sequence":"additional","affiliation":[]},{"given":"Mario","family":"Tanda","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2008,9,12]]},"reference":[{"key":"e_1_2_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/JOE.1987.1145247"},{"key":"e_1_2_1_3_2","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1109\/TIT.1981.1056414","article-title":"Detection of weak signals in non\u2010Gaussian noise","volume":"27","author":"Lu N. H.","year":"1981","journal-title":"IEEE Trans. Inform. Theory"},{"key":"e_1_2_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCOM.1984.1096174"},{"key":"e_1_2_1_5_2","unstructured":"L.Izzo L.Paura M.Tanda:Signal interception in non\u2010Gaussian noise. To be published in \u201cIEEE Trans. Commun.\u201d."},{"key":"e_1_2_1_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-3834-8"},{"key":"e_1_2_1_7_2","volume-title":"Fondements th\u00e9oriques de la radiotechnique statistique","author":"Levin B.","year":"1976"},{"key":"e_1_2_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCOM.1986.1096497"},{"key":"e_1_2_1_9_2","unstructured":"D.Middleton A. D.Spaulding:Optimum reception in non\u2010Gaussian electromagnetic interference environments. Pt. II: Optimum and suboptimum threshold signal detection in class A and B noise. NTIA Tech. Rep. 83\u2010120 U.S. Dept. of Commerce Washington D.C. 1983."},{"key":"e_1_2_1_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/JOE.1987.1145228"},{"key":"e_1_2_1_11_2","doi-asserted-by":"publisher","DOI":"10.1002\/ett.4460010302"},{"key":"e_1_2_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/29.17502"},{"key":"e_1_2_1_13_2","doi-asserted-by":"publisher","DOI":"10.1121\/1.398700"},{"key":"e_1_2_1_14_2","volume-title":"Statistical spectral analysis: a nonprobabilistic theory","author":"Gardner W. 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