{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T01:47:42Z","timestamp":1779155262667,"version":"3.51.4"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2019,5,23]],"date-time":"2019-05-23T00:00:00Z","timestamp":1558569600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,5,23]],"date-time":"2019-05-23T00:00:00Z","timestamp":1558569600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2019,6]]},"DOI":"10.1007\/s00521-019-04261-2","type":"journal-article","created":{"date-parts":[[2019,5,23]],"date-time":"2019-05-23T14:05:07Z","timestamp":1558620307000},"page":"1967-1981","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Deep long short-term memory networks-based automatic recognition of six different digital modulation types under varying noise conditions"],"prefix":"10.1007","volume":"31","author":[{"given":"Nihat","family":"Daldal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u00d6zal","family":"Y\u0131ld\u0131r\u0131m","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kemal","family":"Polat","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,5,23]]},"reference":[{"key":"4261_CR1","first-page":"545","volume":"4","author":"H Altun","year":"2010","unstructured":"Altun H, \u00d6zt\u00fcrk Y, Proakis JG, Masoud S (2010) Fundamentals of communication systems. Nobel Yay\u0131n 4:545\u2013567","journal-title":"Nobel Yay\u0131n"},{"key":"4261_CR2","doi-asserted-by":"crossref","unstructured":"Almohamad TA, Mohd Salleh MF, Mahmud MN, and Sa\u2019 DAHY (2018) Simultaneous determination of modulation types and signal-to-noise ratios using feature-based approach. In: IEEE access, vol 6, pp 9262\u20139271","DOI":"10.1109\/ACCESS.2018.2809448"},{"key":"4261_CR3","doi-asserted-by":"crossref","unstructured":"Dai A, Zhang H, Sun H (2016) Automatic modulation classification using stacked sparse auto-encoders. In: 2016 IEEE 13th international conference on signal processing (ICSP), Chengdu, pp 248\u2013252","DOI":"10.1109\/ICSP.2016.7877834"},{"issue":"1","key":"4261_CR4","first-page":"75","volume":"25","author":"A Fan","year":"2017","unstructured":"Fan A, Fan Y (2017) Unsupervised feature learning and automatic modulation classification using deep learning model. Phys Commun 25(1):75\u201384","journal-title":"Phys Commun"},{"key":"4261_CR5","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.dsp.2017.09.005","volume":"71","author":"A Afan","year":"2017","unstructured":"Afan A, Fan Y, Liu S (2017) Automatic modulation classification of digital modulation signals with stacked autoencoders. Digit Signal Process 71:108\u2013116","journal-title":"Digit Signal Process"},{"issue":"9","key":"4261_CR6","first-page":"563","volume":"9","author":"A Kubankova","year":"2010","unstructured":"Kubankova A, Kubanek D (2010) Algorithms of digital modulation classification and their verification. WSEAS Trans Commun 9(9):563\u2013572","journal-title":"WSEAS Trans Commun"},{"key":"4261_CR7","unstructured":"Ert\u00fcrk S (2016) Say\u0131sal Haberle\u015fme, Birsen Yay\u0131nevi, \u0130stanbul, T\u00fcrkiye"},{"issue":"12","key":"4261_CR8","first-page":"107","volume":"3","author":"S Jain","year":"2015","unstructured":"Jain S, Yadav S (2015) A survey paper on digital modulation techniques. Int J Comput Sci Eng Surv Pap 3(12):107\u2013111","journal-title":"Int J Comput Sci Eng Surv Pap"},{"issue":"03","key":"4261_CR9","first-page":"85","volume":"12","author":"OA Adeleke","year":"2012","unstructured":"Adeleke OA, Abolade RO (2012) Modulation methods employed in digital communication: an analysis. Int J Electr Comput Sci IJECS-IJENS 12(03):85\u201393","journal-title":"Int J Electr Comput Sci IJECS-IJENS"},{"key":"4261_CR10","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1016\/j.phycom.2018.12.019","volume":"34","author":"W Li","year":"2019","unstructured":"Li W, Dou Z, Qi L, Shi C (2019) Wavelet transform based modulation classification for 5G and UAV communication in multipath fading channel. Phys Commun 34:272\u2013282","journal-title":"Phys Commun"},{"key":"4261_CR11","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.compind.2019.04.005","volume":"109","author":"N Daldal","year":"2019","unstructured":"Daldal N, Polat K, Guo Y (2019) Classification of multi-carrier digital modulation signals using NCM clustering based feature-weighting method. Comput Ind 109:45\u201358","journal-title":"Comput Ind"},{"issue":"2\u20133","key":"4261_CR12","first-page":"195","volume":"7","author":"JL Elman","year":"1991","unstructured":"Elman JL (1991) Distributed representations, simple recurrent networks, and grammatical structure. Mach Learn 7(2\u20133):195\u2013225","journal-title":"Mach Learn"},{"key":"4261_CR13","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1207\/s15516709cog1402_1","volume":"14","author":"JL Elman","year":"1990","unstructured":"Elman JL (1990) Finding structure in time. Cogn Sci 14:179\u2013211","journal-title":"Cogn Sci"},{"key":"4261_CR14","unstructured":"https:\/\/towardsdatascience.com\/recurrent-neural-networks-and-lstm-4b601dd822a5\n                    \n                  . Last accessed: February, 2019"},{"key":"4261_CR15","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9:1735\u20131780","journal-title":"Neural Comput"},{"key":"4261_CR16","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.compbiomed.2018.03.016","volume":"96","author":"\u00d6 Yildirim","year":"2018","unstructured":"Yildirim \u00d6 (2018) A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification. Comput Biol Med 96:189\u2013202","journal-title":"Comput Biol Med"},{"key":"4261_CR17","doi-asserted-by":"crossref","unstructured":"Cheng J, Dong L, Lapata M (2016) Long short-term memory-networks for machine reading. \n                    arXiv:1601.06733","DOI":"10.18653\/v1\/D16-1053"},{"key":"4261_CR18","unstructured":"Sak H, Senior A, Beaufays F (2014) Long short-term memory based recurrent neural network architectures for large vocabulary speech recognition. \n                    arXiv:1402.1128"},{"key":"4261_CR19","doi-asserted-by":"crossref","unstructured":"Kim B, Kim J, Chae H, Yoon D, Choi JW (2016) Deep neural network-based automatic modulation classification technique. In: 2016 International conference on information and communication technology convergence (ICTC), Jeju, pp 579\u2013582","DOI":"10.1109\/ICTC.2016.7763537"},{"key":"4261_CR20","doi-asserted-by":"crossref","unstructured":"Li J, Meng Q, Zhang G, Sun Y, Qiu L, Ma W (2017) Automatic modulation classification using support vector machines and error correcting output codes. In: 2017 IEEE 2nd information technology, networking, electronic and automation control conference (ITNEC), Chengdu, pp 60\u201363","DOI":"10.1109\/ITNEC.2017.8284863"},{"key":"4261_CR21","doi-asserted-by":"publisher","first-page":"5607","DOI":"10.1109\/ACCESS.2018.2794587","volume":"6","author":"K Zhang","year":"2018","unstructured":"Zhang K, Xu EL, Feng Z, Zhang P (2018) A dictionary learning based automatic modulation classification method. IEEE Access 6:5607\u20135617","journal-title":"IEEE Access"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04261-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04261-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04261-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,21]],"date-time":"2020-05-21T23:23:33Z","timestamp":1590103413000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04261-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,23]]},"references-count":21,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2019,6]]}},"alternative-id":["4261"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04261-2","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,23]]},"assertion":[{"value":"25 October 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 May 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 May 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"We declare that there is no conflict of interest anywhere.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}