{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:27:47Z","timestamp":1740202067541,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"abstract":"<jats:p>A new triple correlation function&amp;ndash;sparse autoencoder (TCF&amp;ndash;SAE) algorithm based on SAE for m-sequence recognition is proposed. First, the peak characteristic of the TCF of m-sequences is introduced. The peak characteristic is found to be well kept irrespective of periodic or aperiodic m-sequence. Second, a construction method of input sample for network based on the TCF characteristic of m-sequence is proposed. Finally, a feature learning network is constructed by a SAE, and the learned features are classified by softmax regression. A network model with optimal recognition performance is then obtained by simulation experiments with different numbers of hidden layers and hidden units. The results show that the proposed TCF-SAE algorithm for the m-sequence classification is effective and displays a good recognition performance at low signal-to-noise ratio.<\/jats:p>","DOI":"10.3233\/978-1-61499-927-0-252","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:27:24Z","timestamp":1740133644000},"source":"Crossref","is-referenced-by-count":0,"title":["TCF&amp;ndash;SAE Algorithm for m-Sequence Recognition"],"prefix":"10.3233","author":[{"family":"Qiang Fangfang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Zhao Zhijin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Chen Ying","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Shen Lei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Jiang Xianyang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining IV"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:13:23Z","timestamp":1740136403000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-926-3&spage=252&doi=10.3233\/978-1-61499-927-0-252"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-927-0-252","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2018]]}}}