A NEW MODEL OF FEEDFORWARD NEURAL NETWORKS

被引:1
|
作者
WANG, DX
TAI, JW
机构
[1] Institute of Automation, Academia Sinica, 2728 Beijing, P.O. Box
基金
中国国家自然科学基金;
关键词
D O I
10.1016/0375-9601(92)90957-N
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
A new model of multilayer neural networks based on the back-propagation algorithm is presented. The network is a modified version of the STBP model, and employs an output layer with hard threshold function neurons; the model is very efficient; the learning speed can be improved. The model has an efficient ability to approximate any practical function, and is suitable for optical implementation.
引用
收藏
页码:41 / 44
页数:4
相关论文
共 50 条
  • [21] Extreme learning machine: A new learning scheme of feedforward neural networks
    Huang, GB
    Zhu, QY
    Siew, CK
    [J]. 2004 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS, 2004, : 985 - 990
  • [22] A new optimization algorithm for single hidden layer feedforward neural networks
    Li, Leong Kwan
    Shao, Sally
    Yiu, Ka-Fai Cedric
    [J]. APPLIED SOFT COMPUTING, 2013, 13 (05) : 2857 - 2862
  • [23] New error function for single hidden layer feedforward neural networks
    Li, Leong Kwan
    Lee, Richard Chak Hong
    [J]. CISP 2008: FIRST INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOL 5, PROCEEDINGS, 2008, : 752 - 755
  • [24] New algorithm of optimization layer by layer about feedforward neural networks
    Zhang, Daiyuan
    [J]. Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence, 2000, 13 (01): : 103 - 105
  • [25] Oscillation Characteristics of Feedforward Neural Networks
    Li, Yudi
    Wu, Aiguo
    Dong, Na
    Du, Lijia
    Chai, Yi
    [J]. 2018 13TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2018, : 1074 - 1079
  • [26] Randomized Algorithms for Feedforward Neural Networks
    Li Fan-jun
    Li Ying
    [J]. PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016, 2016, : 3664 - 3668
  • [27] Channel equalization by feedforward neural networks
    Lu, B
    Evans, BL
    [J]. ISCAS '99: PROCEEDINGS OF THE 1999 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL 5: SYSTEMS, POWER ELECTRONICS, AND NEURAL NETWORKS, 1999, : 587 - 590
  • [28] Feedforward neural networks for compound signals
    Szczuka, Marcin
    Slezak, Dominik
    [J]. THEORETICAL COMPUTER SCIENCE, 2011, 412 (42) : 5960 - 5973
  • [29] Interpolation functions of feedforward neural networks
    Li, HX
    Lee, ES
    [J]. COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2003, 46 (12) : 1861 - 1874
  • [30] Feedforward neural networks without orthonormalization
    Chen, Lei
    Pung, Hung Keng
    Long, Fei
    [J]. ICEIS 2007: PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS: ARTIFICIAL INTELLIGENCE AND DECISION SUPPORT SYSTEMS, 2007, : 420 - 423