137 related articles for article (PubMed ID: 11771719)
1. Improvement of generalization ability for identifying dynamical systems by using universal learning networks.
Hirasawa K; Kim S; Hu J; Murata J; Han M; Jin C
Neural Netw; 2001 Dec; 14(10):1389-404. PubMed ID: 11771719
[TBL] [Abstract][Full Text] [Related]
2. Universal learning network and its application to robust control.
Hirasawa K; Murata J; Hu J; Jin C
IEEE Trans Syst Man Cybern B Cybern; 2000; 30(3):419-30. PubMed ID: 18252374
[TBL] [Abstract][Full Text] [Related]
3. Universal learning network and its application to chaos control.
Hirasawa K; Wang X; Murata J; Hu J; Jin C
Neural Netw; 2000 Mar; 13(2):239-53. PubMed ID: 10935763
[TBL] [Abstract][Full Text] [Related]
4. A new control method of nonlinear systems based on impulse responses of universal learning networks.
Hirasawa K; Hu J; Murata J; Jin C
IEEE Trans Syst Man Cybern B Cybern; 2001; 31(3):362-72. PubMed ID: 18244799
[TBL] [Abstract][Full Text] [Related]
5. Propagation and control of stochastic signals through universal learning networks.
Hirasawa K; Mabu S; Hu J
Neural Netw; 2006 May; 19(4):487-99. PubMed ID: 16423502
[TBL] [Abstract][Full Text] [Related]
6. A learning rule for very simple universal approximators consisting of a single layer of perceptrons.
Auer P; Burgsteiner H; Maass W
Neural Netw; 2008 Jun; 21(5):786-95. PubMed ID: 18249524
[TBL] [Abstract][Full Text] [Related]
7. Fuzzy wavelet neural network models for prediction and identification of dynamical systems.
Yilmaz S; Oysal Y
IEEE Trans Neural Netw; 2010 Oct; 21(10):1599-609. PubMed ID: 20813638
[TBL] [Abstract][Full Text] [Related]
8. Finite time convergent learning law for continuous neural networks.
Chairez I
Neural Netw; 2014 Feb; 50():175-82. PubMed ID: 24321615
[TBL] [Abstract][Full Text] [Related]
9. Predictive control of nonlinear systems based on identification by backpropagation networks.
Hao J; Vandewalle J; Tan S
Int J Neural Syst; 1994 Dec; 5(4):335-44. PubMed ID: 7711964
[TBL] [Abstract][Full Text] [Related]
10. Generalized multiscale radial basis function networks.
Billings SA; Wei HL; Balikhin MA
Neural Netw; 2007 Dec; 20(10):1081-94. PubMed ID: 17993257
[TBL] [Abstract][Full Text] [Related]
11. Adaptive control of uncertain nonaffine nonlinear systems with input saturation using neural networks.
Esfandiari K; Abdollahi F; Talebi HA
IEEE Trans Neural Netw Learn Syst; 2015 Oct; 26(10):2311-22. PubMed ID: 25532213
[TBL] [Abstract][Full Text] [Related]
12. A dynamical model for the analysis and acceleration of learning in feedforward networks.
Ampazis N; Perantonis SJ; Taylor JG
Neural Netw; 2001 Oct; 14(8):1075-88. PubMed ID: 11681752
[TBL] [Abstract][Full Text] [Related]
13. Improving generalization performance of natural gradient learning using optimized regularization by NIC.
Park H; Murata N; Amari S
Neural Comput; 2004 Feb; 16(2):355-82. PubMed ID: 15006100
[TBL] [Abstract][Full Text] [Related]
14. Noise, regularizers, and unrealizable scenarios in online learning from restricted training sets.
Xiong YS; Saad D
Phys Rev E Stat Nonlin Soft Matter Phys; 2001 Jul; 64(1 Pt 1):011919. PubMed ID: 11461300
[TBL] [Abstract][Full Text] [Related]
15. Effective neural network ensemble approach for improving generalization performance.
Yang J; Zeng X; Zhong S; Wu S
IEEE Trans Neural Netw Learn Syst; 2013 Jun; 24(6):878-87. PubMed ID: 24808470
[TBL] [Abstract][Full Text] [Related]
16. Universal approximation of extreme learning machine with adaptive growth of hidden nodes.
Zhang R; Lan Y; Huang GB; Xu ZB
IEEE Trans Neural Netw Learn Syst; 2012 Feb; 23(2):365-71. PubMed ID: 24808516
[TBL] [Abstract][Full Text] [Related]
17. Decentralized neural identifier and control for nonlinear systems based on extended Kalman filter.
CastaƱeda CE; Esquivel P
Neural Netw; 2012 Jul; 31():81-7. PubMed ID: 22503780
[TBL] [Abstract][Full Text] [Related]
18. A neural observer with time-varying learning rate: analysis and applications.
Gurubel KJ; Alanis AY; Sanchez EN; Carlos-Hernandez S
Int J Neural Syst; 2014 Feb; 24(1):1450011. PubMed ID: 24344696
[TBL] [Abstract][Full Text] [Related]
19. A new formulation for feedforward neural networks.
Razavi S; Tolson BA
IEEE Trans Neural Netw; 2011 Oct; 22(10):1588-98. PubMed ID: 21859600
[TBL] [Abstract][Full Text] [Related]
20. Global asymptotic stability of Hopfield neural network involving distributed delays.
Zhao H
Neural Netw; 2004 Jan; 17(1):47-53. PubMed ID: 14690706
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]