Wideband Wireless Transmitter Identification Based on Hammerstein-Wiener Model

被引:0
|
作者
Sun, Minhong [1 ]
Xu, Tiancheng [1 ]
Guo, Hongchen [1 ]
Zhong, Hua [1 ]
机构
[1] Hangzhou Dianzi Univ, Dept Commun Engn, Hangzhou 310018, Zhejiang, Peoples R China
来源
关键词
Transmitter Identification; System Identification; Hammerstein-Wiener Model; Genetic Algorithm;
D O I
10.6180/jase.201806_21(2).0014
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:261 / 269
页数:9
相关论文
共 50 条
  • [21] A Robust Hammerstein-Wiener Model Identification Method for Highly Nonlinear Systems
    Sun, Lijie
    Hou, Jie
    Xing, Chuanjun
    Fang, Zhewei
    PROCESSES, 2022, 10 (12)
  • [22] Model-based predictive control for Hammerstein-Wiener systems
    Bloemen, HHJ
    van den Boom, TJJ
    Verbruggen, HB
    INTERNATIONAL JOURNAL OF CONTROL, 2001, 74 (05) : 482 - 495
  • [23] Identification of Hammerstein-Wiener time delay model based on approximate least absolute deviation
    Xu, Baochang
    Rong, Zhichao
    Wang, Yaxin
    Yuan, Likun
    INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL, 2023, 42 (03) : 251 - 258
  • [24] Two-Stage Shape Memory Alloy Identification Based on the Hammerstein-Wiener Model
    Copaci, Dorin
    Moreno, Luis
    Blanco, Dolores
    FRONTIERS IN ROBOTICS AND AI, 2019, 6
  • [25] Nonlinear System Identification of pH Process using Hammerstein-Wiener Model
    Rattanawaorahirunkul, Rapeepong
    Sanposh, Peerayot
    Panjapornpon, Chanin
    2016 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATIONS (ICEIC), 2016,
  • [26] Identification Approach of Hammerstein-Wiener Model Corrupted by Colored Process Noise
    Li, Feng
    Jia, Li
    Xiong, Qi
    ADVANCED COMPUTATIONAL METHODS IN LIFE SYSTEM MODELING AND SIMULATION, LSMS 2017, PT I, 2017, 761 : 432 - 441
  • [27] Hammerstein-Wiener Model for Wideband RF Transmitters Using Base-Band Data
    Taringou, Farzaneh
    Srinivasan, Balasubrahmanyan
    Malhame, Roland
    Ghannouchi, Fadhel
    2007 ASIA PACIFIC MICROWAVE CONFERENCE, VOLS 1-5, 2007, : 1199 - +
  • [28] Recursive Identification for Hammerstein-Wiener system based on extreme learning machine
    Han, Zhenzhen
    Wang, Yunli
    Zhang, Luyang
    PROCEEDINGS OF 2021 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INFORMATION SYSTEMS (ICAIIS '21), 2021,
  • [29] Hammerstein-Wiener Model Research for a Stewart Platform
    Wang, Xuewei
    Zhang, Wensheng
    Wu, Baolin
    2012 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO 2012), 2012,
  • [30] Multi-Level Identification of Hammerstein-Wiener Systems
    Mzyk, Grzegorz
    Bieganski, Marcin
    Mielcarek, Pawel
    IFAC PAPERSONLINE, 2019, 52 (29): : 174 - 179