{"id":6623,"date":"2026-08-16T21:05:17","date_gmt":"2026-08-16T13:05:17","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=6623"},"modified":"2026-08-23T14:22:08","modified_gmt":"2026-08-23T06:22:08","slug":"wideband-wireless-transmitter-identification-based-on-hammerstein-wiener-model","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=wideband-wireless-transmitter-identification-based-on-hammerstein-wiener-model","title":{"rendered":"Wideband Wireless Transmitter Identification Based on Hammerstein-Wiener Model"},"content":{"rendered":"\n
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<\/i> 2018<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 21, Issue 2<\/a><\/p>\n<\/div>\n\n\n\n

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Minhong Sun, Tiancheng Xu, Hongchen Guo, Hua Zhong<\/i><\/a><\/p>\n\n\n\n

Department of Communication Engineering, Hangzhou Dianzi University, Hangzhou 310018, P.R. China<\/p>\n<\/div>\n\n\n\n

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Received:\u00a0April 29, 2016
Accepted:\u00a0March 11, 2018
Publication Date:\u00a0August 16, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

Flow chart of the improved GA.<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:  BibTeX <\/a>| https:\/\/doi.org\/10.6180\/jase.201806_21(2).0014<\/a>  <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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In recent years, the identification of the same-model wideband wireless transmitter manufactured by a same manufacturer has emerged as a big challenge. In this paper, a model-based approach is proposed for the identification of the same type wideband wireless transmitter. A Hammerstein-Wiener model is adopted for modeling the wideband wireless transmitter and an improved genetic algorithm is proposed for identifying the model. The estimated model parameters are taken as a feature vector for the identification of the wideband wireless transmitter. The simulation results verify the effectiveness of the proposed method. Moreover, the improved genetic algorithm achieves better estimation precision and higher identification rate than the basic genetic algorithm, the classic least squares iteration method, the AWPSO and the neural network algorithm.<\/p>\n\n\n\n

Keywords: Transmitter Identification; System Identification; Hammerstein-Wiener Model; Genetic Algorithm<\/em><\/p>\n\n\n\n

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