An adaptive wavelet network for function learning

Neural Computing and Applications

Volumn 19, Issue 3, 2010, Pages 383-392

  Oysal, Yusuf ^a   Yilmaz, Sevcan ^a  

^a ANADOLU UNIVERSITY   (Turkey)

Author keywords

Function approximation; Radial basis function networks; Wavelet neural networks

Indexed keywords

EID: 77952876761     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-009-0297-4     Document Type: Article

References (36)

1. Zhang Q (1997) Using wavelet networks in nonparametric estimation. IEEE Trans Neural Netw 8: 227-336. doi: 10. 1109/72. 557660.
2. Zhang Q, Benveniste A (1992) Wavelet networks. IEEE Trans Neural Netw 3: 889-898. doi: 10. 1109/72. 165591.
3. Zhang J, Walter GG, Lee WNW (1995) Wavelet neural networks for function learning. IEEE Trans Signal Process 43: 1485-1497. doi: 10. 1109/78. 388860.
4. Ho Daniel WC, Zhang PA, Jinhua X (2001) Fuzzy wavelet networks for function learning. IEEE Trans Fuzzy Syst 9: 200-211. doi: 10. 1109/91. 917126.
5. Kim J, Kasabov N (1999) HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems. Neural Netw 12: 1301-1319. doi: 10. 1016/S0893-6080(99)00067-2.
6. Jang JSR (1993) ANFIS: adaptive-network-based fuzzy inference systems. IEEE Trans Syst Man Cybern 23(3): 665-685. doi: 10. 1109/21. 256541.
7. Horikawa S, Furuhashi T, Uchikawa Y (1992) On fuzzy modeling using fuzzy neural networks with the back-propagation algorithm. IEEE Trans Neural Netw 3(5): 801-806. doi: 10. 1109/72. 159069.
8. Leonard J, Kramer M (1991) Radial basis function networks for classifying process faults. IEEE Control Syst 11: 31-38. doi: 10. 1109/37. 75576.
9. Tan Y, Dang X, Liang F, Su CY (2000) Dynamic wavelet neural network for nonlinear dynamic system identification. In: Proceedings of the 2000 IEEE, international conference on control applications.
10. Mallat S (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(7): 674-693. doi: 10. 1109/34. 192463.
11. Sanner R, Slotine J-JE (1992) Gaussian networks for direct adaptive control. IEEE Trans Neural Netw 13(6): 837-863. doi: 10. 1109/72. 165588.
12. Ljung L (1987) System identification: theory for the user. Prentice-Hall, Englewood Cliffs.
13. Strobach P (1990) Linear prediction theory: a mathematical basis for adaptive systems. Springer, New York.
14. Gholizadeh S, Salajegheh E, Torkzadeh P (2008) Structural optimization with frequency constraints by genetic algorithm using wavelet radial basis function neural network. J Sound Vibrat 312: 316-331. doi: 10. 1016/j. jsv. 2007. 10. 050.
15. Gill PE, Murray W, Wright MH (1993) Practical optimization. Academic Press Ltd, London.
16. Chen J, Bruns DD (1995) WaveARX neural network development for system identification using a systematic design synthesis. Ind Eng Chem Res 34: 4420-4435. doi: 10. 1021/ie00039a034.
17. Box GEP (1970) Time series analysis, forecasting and control. Holden Day, San Francisco.
18. Chen Y, Yang B, Dong J (2006) Time-series prediction using a local linear wavelet neural network. Neurocomputing 69: 449-465. doi: 10. 1016/j. neucom. 2005. 02. 006.
19. Tong RM (1980) The evaluation of fuzzy models derived from experimental data. Fuzzy Sets Syst 4: 1-12. doi: 10. 1016/0165-0114(80)90059-7.
20. Pedrycz W (1984) An identification algorithm in fuzzy relational systems. Fuzzy Sets Syst 13: 153-167. doi: 10. 1016/0165-0114(84)90015-0.
21. Xu CW (1987) Fuzzy model identification and self-learning for dynamic systems. IEEE Trans Syst Man Cybern 17: 683-689. doi: 10. 1109/TSMC. 1987. 289361.
22. Sugeno M et al (1991) Linguistic modeling based on numerical data. Proc IFSA 91: 234-247.
23. Surmann H et al (1993) Self-organizing and genetic algorithm for an automatic design of fuzzy control and decision systems. Proc FUFIT's 93: 1079-1104.
24. Jang JSR et al (1997) Neuro-fuzzy and Soft computing: a computational approach to learning and machine intelligence. Prentice-Hall, Upper Saddle river.
25. Kasabov NK et al (1997) FuNN/2-A fuzzy neural network architecture for adaptive learning and knowledge acquisition. Inf Sci 101: 155-175. doi: 10. 1016/S0020-0255(97)00007-8.
26. Chen YH et al (2004) Nonlinear system modeling via optimal design of neural trees. Int J Neural Syst 14(2): 125-137. doi: 10. 1142/S0129065704001905.
27. Mackey M, Glass L (1977) Oscillation and chaos in physiological control systems. Science 197: 287-289. doi: 10. 1126/science. 267326.
28. Wang LX et al (1992) Generating fuzzy rules by learning from examples. IEEE Trans Fuzzy Syst Man Cybern 22: 1414-1427. doi: 10. 1109/21. 199466.
29. Cho KB et al (1995) Radial basis function based adaptive fuzzy systems their application to system identification and prediction. Fuzzy Sets Syst 83: 325-339. doi: 10. 1016/0165-0114(95)00322-3.
30. Rojas I et al (2002) Time series analysis using normalized PG-RBF network with regression weights. Neurocomputing 42: 167-285. doi: 10. 1016/S0925-2312(01)00338-1.
31. Kim D et al (1997) Forecasting time series with genetic fuzzy predictor ensembles. IEEE Trans Fuzzy Syst 5(2): 523-535.
32. Narendra KS, Parthasarathy K (1990) Identification and control dynamical systems using neural networks. IEEE Trans Neural Netw 1(1): 4-27. doi: 10. 1109/72. 80202.
33. Abiyev RH, Kaynak O (2008) Fuzzy wavelet neural network for identification and control of dynamic plants-a novel structure and comparative study. IEEE Trans Ind Electron 55(8): 3133-3140. doi: 10. 1109/TIE. 2008. 924018.
34. Elman JL (1990) Finding structure in time. Cogn Sci 14(2): 179-211.
35. Juang CF, Lin CT (1999) A recurrent self-organizing neural fuzzy inference network. IEEE Trans Neural Netw 10(4): 828-845. doi: 10. 1109/72. 774232.
36. Juang C-F (2002) A TSK-type recurrent fuzzy network for dynamic systems processing by neural network and genetic algorithms. IEEE Trans Fuzzy Syst 10(2): 155-170. doi: 10. 1109/91. 995118.