An adaptive neuro-fuzzy system for efficient implementations

被引：18
|
作者：
Echanobe, J. [1 ]
del Campo, I. [1 ]
Bosque, G. [1 ]
机构：
[1] Univ Basque Country, Dept Elect & Elect, Leioa 48940, Vizcaya, Spain
来源：
INFORMATION SCIENCES | 2008年 / 178卷 / 09期
关键词：
neuro-fuzzy systems; hardware implementations; embedded systems; non-linear systems;
D O I：
10.1016/j.ins.2007.12.009
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 system specially suited for efficient implementations is presented. The system is of the same type as the well-known "adaptive network-based fuzzy inference system" (ANFIS) method. However, different restrictions are applied to the system that considerably reduce the complexity of the inference mechanism. Hence, efficient implementations can be developed. Some experiments are presented which demonstrate the good performance of the proposed system despite its restrictions. Finally, an efficient digital hardware implementation is presented for a two-input single-output neuro-fuzzy system. (c) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码：2150 / 2162
页数：13
相关论文
共 50 条
  • [1] Efficient hardware/software implementation of an adaptive neuro-fuzzy system
    del Campo, Ines
    Echanobe, Javier
    Bosque, Guillermo
    Manuel Tarela, Jose
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2008, 16 (03) : 761 - 778
  • [2] An adaptive neuro-fuzzy approach for system modeling
    Ouyang, CS
    Lee, WJ
    Lee, SJ
    [J]. 2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS, 2002, : 1875 - 1880
  • [3] Improved adaptive neuro-fuzzy inference system
    Benmiloud, Tarek
    [J]. NEURAL COMPUTING & APPLICATIONS, 2012, 21 (03): : 575 - 582
  • [4] Multioutput Adaptive Neuro-fuzzy Inference System
    Benmiloud, T.
    [J]. RECENT ADVANCES IN NEURAL NETWORKS, FUZZY SYSTEMS & EVOLUTIONARY COMPUTING, 2010, : 94 - 98
  • [5] Improved adaptive neuro-fuzzy inference system
    Tarek Benmiloud
    [J]. Neural Computing and Applications, 2012, 21 : 575 - 582
  • [6] ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR END MILLING
    Markopoulos, Angelos P.
    Georgiopoulos, Sotirios
    Kinigalakis, Myron
    Manolakos, Dimitrios E.
    [J]. JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY, 2016, 11 (09) : 1234 - 1248
  • [7] Adaptive Neuro-Fuzzy Inference System for drought forecasting
    Bacanli, Ulker Guner
    Firat, Mahmut
    Dikbas, Fatih
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2009, 23 (08) : 1143 - 1154
  • [8] The adaptive dynamic clustering neuro-fuzzy system for classification
    Napook, Phichit
    Eiamkanitchat, Narissara
    [J]. Lecture Notes in Electrical Engineering, 2015, 339 : 721 - 728
  • [9] Adaptive Neuro-Fuzzy Controller for Vehicle Suspension System
    Kalaivani, R.
    Lakshmi, P.
    [J]. 2013 FIFTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING (ICOAC), 2013, : 236 - 240
  • [10] Neuro-fuzzy system for adaptive multilevel image segmentation
    Boskovitz, V
    Guterman, H
    [J]. NINETEENTH CONVENTION OF ELECTRICAL AND ELECTRONICS ENGINEERS IN ISRAEL, 1996, : 208 - 211
12345