Analysis of hidden layer weights in a dynamic locally recurrent network

被引:0
|
作者
Back, A.D.
Tsoi, A.C.
机构
关键词
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [1] Emergence of clusters in the hidden layer of a dynamic recurrent neural network
    Draye, JP
    Cheron, G
    Libert, G
    Godaux, E
    BIOLOGICAL CYBERNETICS, 1997, 76 (05) : 365 - 374
  • [2] A recurrent network with stochastic weights
    Zhao, JY
    ShaweTaylor, J
    ICNN - 1996 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS. 1-4, 1996, : 1302 - 1307
  • [3] A context layered locally recurrent neural network for dynamic system identification
    Coban, Ramazan
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2013, 26 (01) : 241 - 250
  • [4] Observer design for the single hidden layer fuzzy recurrent wavelet neural network
    Wen, Xin
    Li, Xin
    Wang, Ershen
    Dianbo Kexue Xuebao/Chinese Journal of Radio Science, 2015, 30 (06): : 1197 - 1204
  • [5] Adaptive Global Sliding-Mode Control for Dynamic Systems Using Double Hidden Layer Recurrent Neural Network Structure
    Chu, Yundi
    Fei, Juntao
    Hou, Shixi
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 31 (04) : 1297 - 1309
  • [6] Optimization analysis of dynamic sample number and hidden layer node number based on BP neural network
    Xu, Chunyun
    Xu, Chuanfang
    Advances in Intelligent Systems and Computing, 2013, 212 : 687 - 695
  • [7] Bernoulli Neural Network with Weights Directly Determined and with the Number of Hidden-Layer Neurons Automatically Determined
    Zhang, Yunong
    Ruan, Gongqin
    ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 1, PROCEEDINGS, 2009, 5551 : 36 - 45
  • [8] Factorised Hidden Layer Based Domain Adaptation for Recurrent Neural Network Language Models
    Hentschel, Michael
    Delcroix, Marc
    Ogawa, Atsunori
    Iwata, Tomoharu
    Nakatani, Tomohiro
    2018 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC), 2018, : 1940 - 1944
  • [9] Exploring Classification, Clustering, and Its Limits in a Compressed Hidden Space of a Single Layer Neural Network with Random Weights
    Xie, Meiyan
    Roshan, Usman
    ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2019, PT I, 2019, 11506 : 507 - 516
  • [10] A HYBRID LEARNING NEURAL-NETWORK ARCHITECTURE WITH LOCALLY ACTIVATED HIDDEN LAYER FOR FAST AND ACCURATE MAPPING
    OH, SY
    CHOI, DH
    LEE, IS
    NEUROCOMPUTING, 1995, 7 (03) : 211 - 224