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The special features of the procedure are the possibility to adapt it dynamically to nearly all modulation types, and the capability to identify. The developed scheme based on wavelet transform and statistical parameters has been used to identify M\u2010ary PSK, M\u2010ary QAM, GMSK, and M\u2010ary FSK modulations. The simulated results show that the correct modulation identification is possible to a lower bound of 5\u2009dB. The identification percentage has been analyzed based on the confusion matrix. When SNR is above 5\u2009dB, the probability of detection of the proposed system is more than 0.968. The performance of the proposed scheme has been compared with existing methods and found it will identify all digital modulation schemes with low SNR.<\/jats:p>","DOI":"10.1155\/2008\/175236","type":"journal-article","created":{"date-parts":[[2008,5,15]],"date-time":"2008-05-15T14:19:33Z","timestamp":1210861173000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Digital Modulation Identification Model Using  Wavelet Transform and Statistical Parameters"],"prefix":"10.1155","volume":"2008","author":[{"given":"P.","family":"Prakasam","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M.","family":"Madheswaran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2008,5,11]]},"reference":[{"key":"e_1_2_6_1_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2469-1"},{"key":"e_1_2_6_2_2","doi-asserted-by":"publisher","DOI":"10.1049\/iet-com:20050176"},{"key":"e_1_2_6_3_2","doi-asserted-by":"crossref","unstructured":"DruckmannI. 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