Monopulse amplitude direction-finding using neuro-fuzzy approach

被引：6
|
作者：
Bokshtein, E
Shmaltz, D
Herbst, O
Bunke, H
Kandel, A
机构：
[1] Univ S Florida, Dept Comp Sci & Engn, Tampa, FL 33620 USA
[2] Tel Aviv Univ, Dept Elect Engn Syst, IL-69978 Tel Aviv, Israel
[3] Univ Bern, Inst Informat & Angewandte Math, CH-3012 Bern, Switzerland
来源：
ROBOTICS AND AUTONOMOUS SYSTEMS | 2000年 / 33卷 / 2-3期
关键词：
fuzzy sets; ANFIS; FIS; monopulse amplitude; direction finding;
D O I：
10.1016/S0921-8890(00)00083-X
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A neuro-fuzzy approach for solving the monopulse amplitude direction-finding is proposed. A system comprised of an adaptive network based fuzzy inference system (ANFIS) implementation is simulated and compared to the classic solution of the problem. This comparison is done over a variety of antennas and gain situations, in which the system has to adjust to a change in its basic parameters. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：125 / 134
页数：10
相关论文
共 50 条
  • [21] A neuro-fuzzy approach to agglomerative clustering
    Joshi, A
    Ramakrishnan, N
    Rice, JR
    Houstis, EN
    ICNN - 1996 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS. 1-4, 1996, : 1028 - 1033
  • [22] A neuro-fuzzy approach in parts clustering
    Pai, PF
    PEACHFUZZ 2000 : 19TH INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS, 2000, : 138 - 142
  • [23] A neuro-fuzzy approach to face recognition
    Neagoe, VE
    Iatan, IF
    6TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL XIV, PROCEEDINGS: IMAGE, ACOUSTIC, SPEECH AND SIGNAL PROCESSING III, 2002, : 120 - 125
  • [24] A neuro-fuzzy approach in student modeling
    Stathacopoulou, R
    Grigoriadou, M
    Magoulas, GD
    Mitropoulos, D
    USER MODELING 2003, PROCEEDINGS, 2003, 2702 : 337 - 341
  • [25] Method for Estimating the Number of Radiation Sources in the Problem of the Amplitude Monopulse Direction Finding
    Loginov, A. A.
    Morozov, O. A.
    Semenova, M. Yu.
    Fidelman, V. R.
    RADIOPHYSICS AND QUANTUM ELECTRONICS, 2013, 56 (07) : 456 - 463
  • [26] A novel approach to neuro-fuzzy classification
    Ghosh, Ashish
    Shankar, B. Uma
    Meher, Saroj K.
    NEURAL NETWORKS, 2009, 22 (01) : 100 - 109
  • [27] Feature selection: A neuro-fuzzy approach
    Pal, SK
    Basak, J
    De, RK
    ICNN - 1996 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS. 1-4, 1996, : 1197 - 1202
  • [28] A neuro-fuzzy approach for ramp metering
    Bogenberger, K
    Keller, H
    May, AD
    TENTH INTERNATIONAL CONFERENCE ON ROAD TRANSPORT INFORMATION AND CONTROL, 2000, (472): : 101 - 105
  • [29] Sensitivity analysis of economic variables using neuro-fuzzy approach
    Lotfi, E.
    Babrzadeh, S.
    Khosravi, A.
    SCIENTIA IRANICA, 2020, 27 (03) : 1352 - 1359
  • [30] The Muskingum flood routing model using a neuro-fuzzy approach
    Hone-Jay Chu
    KSCE Journal of Civil Engineering, 2009, 13 : 371 - 376
12345