274 related articles for article (PubMed ID: 18256014)
1. The Chebyshev-polynomials-based unified model neural networks for function approximation.
Lee TT; Jeng JT
IEEE Trans Syst Man Cybern B Cybern; 1998; 28(6):925-35. PubMed ID: 18256014
[TBL] [Abstract][Full Text] [Related]
2. Control of magnetic bearing systems via the Chebyshev polynomial-based unified model (CPBUM) neural network.
Jeng JT; Lee TT
IEEE Trans Syst Man Cybern B Cybern; 2000; 30(1):85-92. PubMed ID: 18244731
[TBL] [Abstract][Full Text] [Related]
3. Nonlinear dynamic system identification using Chebyshev functional link artificial neural networks.
Patra JC; Kot AC
IEEE Trans Syst Man Cybern B Cybern; 2002; 32(4):505-11. PubMed ID: 18238146
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Some comparisons of complexity in dictionary-based and linear computational models.
Gnecco G; Kůrková V; Sanguineti M
Neural Netw; 2011 Mar; 24(2):171-82. PubMed ID: 21094023
[TBL] [Abstract][Full Text] [Related]
6. Local coupled feedforward neural network.
Sun J
Neural Netw; 2010 Jan; 23(1):108-13. PubMed ID: 19596550
[TBL] [Abstract][Full Text] [Related]
7. Specification of training sets and the number of hidden neurons for multilayer perceptrons.
Camargo LS; Yoneyama T
Neural Comput; 2001 Dec; 13(12):2673-80. PubMed ID: 11705406
[TBL] [Abstract][Full Text] [Related]
8. Channel selection and classification of electroencephalogram signals: an artificial neural network and genetic algorithm-based approach.
Yang J; Singh H; Hines EL; Schlaghecken F; Iliescu DD; Leeson MS; Stocks NG
Artif Intell Med; 2012 Jun; 55(2):117-26. PubMed ID: 22503644
[TBL] [Abstract][Full Text] [Related]
9. Pipelined chebyshev functional link artificial recurrent neural network for nonlinear adaptive filter.
Zhao H; Zhang J
IEEE Trans Syst Man Cybern B Cybern; 2010 Feb; 40(1):162-72. PubMed ID: 19751995
[TBL] [Abstract][Full Text] [Related]
10. A learning algorithm for adaptive canonical correlation analysis of several data sets.
Vía J; Santamaría I; Pérez J
Neural Netw; 2007 Jan; 20(1):139-52. PubMed ID: 17113263
[TBL] [Abstract][Full Text] [Related]
11. Iterative Chebyshev approximation method for optimal control problems.
Wu D; Yu C; Wang H; Bai Y; Teo KL; Toh KC
ISA Trans; 2024 Jun; ():. PubMed ID: 38926019
[TBL] [Abstract][Full Text] [Related]
12. Inelastic scattering with Chebyshev polynomials and preconditioned conjugate gradient minimization.
Temel B; Mills G; Metiu H
J Phys Chem A; 2008 Mar; 112(12):2728-37. PubMed ID: 18303864
[TBL] [Abstract][Full Text] [Related]
13. A constructive approach for finding arbitrary roots of polynomials by neural networks.
Huang DS
IEEE Trans Neural Netw; 2004 Mar; 15(2):477-91. PubMed ID: 15384540
[TBL] [Abstract][Full Text] [Related]
14. Approximation by fully complex multilayer perceptrons.
Kim T; Adali T
Neural Comput; 2003 Jul; 15(7):1641-66. PubMed ID: 12816570
[TBL] [Abstract][Full Text] [Related]
15. Analysis and test of efficient methods for building recursive deterministic perceptron neural networks.
Elizondo DA; Birkenhead R; Góngora M; Taillard E; Luyima P
Neural Netw; 2007 Dec; 20(10):1095-108. PubMed ID: 17904333
[TBL] [Abstract][Full Text] [Related]
16. A rapid learning and dynamic stepwise updating algorithm for flat neural networks and the application to time-series prediction.
Chen CP; Wan JZ
IEEE Trans Syst Man Cybern B Cybern; 1999; 29(1):62-72. PubMed ID: 18252280
[TBL] [Abstract][Full Text] [Related]
17. On the optimal design of fuzzy neural networks with robust learning for function approximation.
Tsai HH; Yu PT
IEEE Trans Syst Man Cybern B Cybern; 2000; 30(1):217-23. PubMed ID: 18244746
[TBL] [Abstract][Full Text] [Related]
18. Function approximation using fuzzy neural networks with robust learning algorithm.
Wang WY; Lee TT; Liu CL; Wang CH
IEEE Trans Syst Man Cybern B Cybern; 1997; 27(4):740-7. PubMed ID: 18255916
[TBL] [Abstract][Full Text] [Related]
19. Reorganizing knowledge in neural networks: an explanatory mechanism for neural networks in data classification problems.
Narazaki H; Watanabe T; Yamamoto M
IEEE Trans Syst Man Cybern B Cybern; 1996; 26(1):107-17. PubMed ID: 18263010
[TBL] [Abstract][Full Text] [Related]
20. Observer-based adaptive fuzzy-neural control for a class of uncertain nonlinear systems with unknown dead-zone input.
Liu YJ; Zhou N
ISA Trans; 2010 Oct; 49(4):462-9. PubMed ID: 20598305
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]