Structural synthesis of fast two-layer neural networks

被引：1
|
作者：
Dorogov, AY [1 ]
机构：
[1] St Petersburg State Electrotech Univ, St Petersburg, Russia
来源：
CYBERNETICS AND SYSTEMS ANALYSIS | 2000年 / 36卷 / 04期
关键词：
neural networks; two-layer neural networks; fast neural networks (FNNs); dense neural networks; one-rank networks; fast two-layer neural networks; number of degrees of freedom of neural networks; plasticity (trainability) of neural networks; structural synthesis of fast two-layer neural networks;
D O I：
10.1007/BF02667059
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Methods of construction of structural models of fast two-layer neural networks are considered. The methods are based on the criteria of minimum computing operations and maximum degrees of freedom. Optimal structural models of two-layer neural networks are constructed. Illustrative examples are given.
引用
收藏
页码：512 / 519
页数：8
相关论文
共 50 条
  • [31] Convergence of gradient method with momentum for two-layer feedforward neural networks
    Zhang, NM
    Wu, W
    Zheng, GF
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2006, 17 (02): : 522 - 525
  • [32] The VC dimension and pseudodimension of two-layer neural networks with discrete inputs
    Bartlett, PL
    Williamson, RC
    NEURAL COMPUTATION, 1996, 8 (03) : 625 - 628
  • [33] A New Propagator for Two-Layer Neural Networks in Empirical Model Learning
    Lombardi, Michele
    Gualandi, Stefano
    PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING, CP 2013, 2013, 8124 : 448 - 463
  • [34] Synchronizability of two-layer correlation networks
    Wei, Xiang
    Wu, Xiaoqun
    Lu, Jun-An
    Wei, Juan
    Zhao, Junchan
    Wang, Yisi
    CHAOS, 2021, 31 (10)
  • [35] Untrusted Caches in Two-layer Networks
    Zewail, Ahmed A.
    Yener, Aylin
    2019 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2019, : 1 - 5
  • [36] Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization
    Li G.
    Wang G.
    Ding J.
    IEEE Transactions on Information Theory, 2023, 69 (09) : 5921 - 5935
  • [37] On the learning dynamics of two-layer quadratic neural networks for understanding deep learning
    TAN Zhenghao
    CHEN Songcan
    Frontiers of Computer Science, 2022, 16 (03)
  • [38] Cumulant-based blind identification of two-layer feedforward neural networks
    Dai, Xianhua
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2002, 24 (01):
  • [39] New method of training two-layer sigmoid neural networks using regularization
    Krutikov, V. N.
    Kazakovtsev, L. A.
    Shkaberina, G. Sh
    Kazakovtsev, V. L.
    INTERNATIONAL WORKSHOP ADVANCED TECHNOLOGIES IN MATERIAL SCIENCE, MECHANICAL AND AUTOMATION ENGINEERING - MIP: ENGINEERING - 2019, 2019, 537
  • [40] On the learning dynamics of two-layer quadratic neural networks for understanding deep learning
    Zhenghao Tan
    Songcan Chen
    Frontiers of Computer Science, 2022, 16
12345