{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T09:43:09Z","timestamp":1648719789502},"reference-count":11,"publisher":"World Scientific Pub Co Pte Lt","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2008,10]]},"abstract":"<jats:p> Classification of the communication signals has seen under increasing demands. In this paper, we present a new technique that identifies a variety of digital communication signal types. This technique utilizes a radial basis function neural network (RBFN) as the classifier. Swarm intelligence, as an evolutionary algorithm, is used to construct RBFN. A combination of the higher-order moments and the higher-order cumulants up to eight are selected as the features of the considered digital signal types. In conjunction with RBFN, we have used k-fold cross-validation to improve the generalization potentiality. Simulation results show that the proposed technique has high performance for classification of different communication signals even at very low signal-to-noise ratios. <\/jats:p>","DOI":"10.1142\/s0218126608004617","type":"journal-article","created":{"date-parts":[[2009,2,16]],"date-time":"2009-02-16T12:26:09Z","timestamp":1234787169000},"page":"957-971","source":"Crossref","is-referenced-by-count":0,"title":["A NEW TECHNIQUE FOR CLASSIFICATION OF DIGITAL SIGNAL TYPES"],"prefix":"10.1142","volume":"17","author":[{"given":"ATAOLLAH","family":"EBRAHIMZADEH","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering, Noushirvani Institute of Technology, University of Mazandaran, Babol, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ABOLFAZL","family":"RANJBAR","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, Noushirvani Institute of Technology, University of Mazandaran, Babol, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"MEHRDAD","family":"ARDEBLILPOUR","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, Khajeh Nasir Toosi University of Technology, Tehran, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1109\/26.823550"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1016\/S0165-1684(99)00127-9"},{"key":"rf6","doi-asserted-by":"publisher","DOI":"10.1016\/0165-1684(95)00099-2"},{"key":"rf7","doi-asserted-by":"publisher","DOI":"10.1109\/26.837045"},{"key":"rf11","doi-asserted-by":"publisher","DOI":"10.1109\/26.664294"},{"key":"rf16","volume-title":"Digital Communications","author":"Proakis J. G.","year":"1964"},{"key":"rf18","volume-title":"Tensor Methods in Statistics","author":"McCullagh P.","year":"1987"},{"key":"rf20","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(98)00051-3"},{"key":"rf21","doi-asserted-by":"publisher","DOI":"10.1109\/5.58326"},{"key":"rf22","volume-title":"Neural Networks: A Comprehensive Foundation","author":"Haykin S.","year":"1999"},{"key":"rf25","volume-title":"Swarm Intelligence","author":"Kennedy J.","year":"2001"}],"container-title":["Journal of Circuits, Systems and Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218126608004617","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T18:15:12Z","timestamp":1565201712000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218126608004617"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008,10]]},"references-count":11,"journal-issue":{"issue":"05","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[2008,10]]}},"alternative-id":["10.1142\/S0218126608004617"],"URL":"https:\/\/doi.org\/10.1142\/s0218126608004617","relation":{},"ISSN":["0218-1266","1793-6454"],"issn-type":[{"value":"0218-1266","type":"print"},{"value":"1793-6454","type":"electronic"}],"subject":[],"published":{"date-parts":[[2008,10]]}}}