Multilayer perceptrons and radial basis functions are universal robust approximators

被引：0
|
作者：
Lo, JTH [1 ]
机构：
[1] Univ Maryland, Dept Math & Stat, Baltimore, MD 21228 USA
来源：
IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE | 1998年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The standard risk-sensitive (or exponential quadratic) functional used for robust control and filtering for linear systems is generalized. It is then shown that under relatively mild conditions, a function can be approximated, to any desired degree of accuracy with respect to these general risk-sensitive functionals, by a multilayer perceptron or a radial basis function network.
引用
收藏
页码：1311 / 1314
页数：4
相关论文
共 50 条
  • [41] Training Multilayer Perceptrons Via Minimization of Sum of Ridge Functions
    Wei Wu
    Guorui Feng
    Xin Li
    Advances in Computational Mathematics, 2002, 17 : 331 - 347
  • [42] Experimental design of supervisory control functions based on multilayer perceptrons
    Kukolj, DD
    Berko-Pusic, MT
    Atlagic, B
    AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING, 2001, 15 (05): : 425 - 431
  • [43] ReLU Networks Are Universal Approximators via Piecewise Linear or Constant Functions
    Huang, Changcun
    NEURAL COMPUTATION, 2020, 32 (11) : 2249 - 2278
  • [44] Relu networks are universal approximators via piecewise linear or constant functions
    Huang, Changcun
    Neural Computation, 2020, 32 (11): : 2249 - 2278
  • [45] Control of chaotic dynamical systems using radial basis function network approximators
    Kim, KB
    Park, JB
    Choi, YH
    Chen, GR
    INFORMATION SCIENCES, 2000, 130 (1-4) : 165 - 183
  • [46] Hybrid neural network based on transfer functions of multilayer perception and radial basis function
    Dept. of Computer Science and Engineering, Tongji University, Shanghai 200092, China
    不详
    不详
    Jisuanji Gongcheng, 2006, 6 (25-27):
  • [47] Propagation of Uncertainty through Multilayer Perceptrons for Robust Automatic Speech Recognition
    Astudillo, Ramon Fernandez
    da Silva Neto, Joao Paulo
    12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5, 2011, : 468 - 471
  • [48] Efficient and Robust Parallel Mesh Motion Solver Using Radial Basis Functions
    Xu, Chuanfu (xuchuanfu@nudt.edu.cn), 1600, American Society of Civil Engineers (ASCE), United States (31):
  • [49] Sequential improvement for robust optimization using an uncertainty measure for radial basis functions
    Havinga, J.
    van den Boogaard, A. H.
    Klaseboer, G.
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2017, 55 (04) : 1345 - 1363
  • [50] Sequential improvement for robust optimization using an uncertainty measure for radial basis functions
    J. Havinga
    A. H. van den Boogaard
    G. Klaseboer
    Structural and Multidisciplinary Optimization, 2017, 55 : 1345 - 1363
12345