KNOWLEDGE-BASED SUPPORT VECTOR SYNTHESIS OF THE MICROSTRIP LINES

被引:21
|
作者
Tokan, N. T. [1 ]
Gunes, F. [1 ]
机构
[1] Yildiz Tech Univ, Fac Elect & Elect, Dept Elect & Commun Engn, TR-34349 Istanbul, Turkey
关键词
NEURAL-NETWORKS; MICROWAVE; DESIGN; OPTIMIZATION; MODELS;
D O I
10.2528/PIER09022704
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we proposed an efficient knowledge-based Support Vector Regression Machine (SVRM) method and applied it to the synthesis of the transmission lines for the microwave integrated circuits, with the highest possible accuracy using the fewest accurate data. The technique has integrated advanced concepts of SVM and knowledge-based modeling into a powerful and systematic framework. Thus, synthesis model as fast as the coarse models and at the same time as accurate as the. ne models is obtained for the RF/Microwave planar transmission lines. The proposed knowledge-based support vector method is demonstrated by a typical worked example of microstrip line. Success of the method and performance of the resulted synthesis model is presented and compared with ANN results.
引用
收藏
页码:65 / 77
页数:13
相关论文
共 50 条
  • [1] A knowledge-based support vector synthesis of the transmission lines for use in microwave integrated circuits
    Gunes, Filiz
    Tokan, Nurhan Tuerker
    Gurgen, Fikret
    EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (04) : 3302 - 3309
  • [2] Analysis and Synthesis of the Microstrip Lines Based on Support Vector Regression
    Tokan, Nurhan Tuerker
    Guenes, Filiz
    2008 EUROPEAN MICROWAVE INTEGRATED CIRCUITS CONFERENCE (EUMIC), 2008, : 446 - 449
  • [3] Analysis and Synthesis of the Microstrip Lines Based on Support Vector Regression
    Tokan, Nurhan Tuerker
    Guenes, Filiz
    2008 EUROPEAN MICROWAVE CONFERENCE, VOLS 1-3, 2008, : 575 - 578
  • [4] Online Knowledge-Based Support Vector Machines
    Kunapuli, Gautam
    Bennett, Kristin P.
    Shabbeer, Amina
    Maclin, Richard
    Shavlik, Jude
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT II: EUROPEAN CONFERENCE, ECML PKDD 2010, 2010, 6322 : 145 - 161
  • [5] Support vector design of the microstrip lines
    Gunes, Filiz
    Tokan, Nurhan Tuerker
    Gurgen, Fikret
    INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, 2008, 18 (04) : 326 - 336
  • [6] Prior Knowledge-Based fuzzy Support Vector Regression
    Wang Ling
    Mu Zhi-Chun
    Guo Hui
    2008 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5, 2008, : 392 - +
  • [7] Knowledge-based Support Vector Classification Based on C-SVC
    Zhang, Chunhua
    Shao, Xiaojian
    Li, Dewei
    FIRST INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT, 2013, 17 : 1083 - 1090
  • [8] Knowledge-Based Green's Kernel for Support Vector Regression
    Farooq, Tahir
    Guergachi, Aziz
    Krishnan, Sridhar
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2010, 2010
  • [9] Knowledge-based linear support vector machine classifier via vector projection
    Wu, Lu
    Lin, Jie
    Journal of Computational Information Systems, 2015, 11 (07): : 2559 - 2569
  • [10] Knowledge-based Support Vector Machine Classifiers via Nearest Points
    Ju, Xuchan
    Tian, Yingjie
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, ICCS 2012, 2012, 9 : 1240 - 1248