Paper Industry, System Identification and Modeling
First published: 27 December 1999
Abstract
The sections in this article are
- 1 Background
- 2 Network Implementations
- 3 Networks Used for this Study
- 4 Experimental Results
- 5 Conclusion
Bibliography
- 1 L. Ljung T. Soderstrom Theory and Practice of Recursive Identification, Cambridge, MA: MIT Press, 1983.
- 2 J. H. Chen D. D. Bruns WaveARX neural network development for system identification using a systematic design synthesis, Ind. Eng. Chem. Res., 34 (12): 4420–4435, 1995.
- 3 M. Vetterli J. Kovacevic Wavelets and Subband Coding, Englewood Cliffs, NJ: Prentice-Hall, 1995.
- 4 R. Young Wavelet Theory and Its Applications, Dordrecht: Kluwer, 1992.
- 5 O. Rioul M. Vetterli Wavelets and signal processing, IEEE Signal Process. Mag., 8 (4): 14–38, 1991.
- 6 R. Duffin A. Schaffer A class of nonharmonic Fourier series, Trans. Am. Math. Soc., 72: 341–353, 1952.
- 7
I. Daubechies
Ten Lectures on Wavelets,
Philadelphia, PA:
Society for Industrial and Applied Mathematics,
1992.
10.1137/1.9781611970104 Google Scholar
- 8
G. Strang
T. Nguyen
Wavelets and Filter Banks,
Wellesley, MA:
Wellesley-Cambridge Press,
1996.
10.1093/oso/9780195094237.003.0002 Google Scholar
- 9 Q. Zhang A. Benveniste Wavelet networks, IEEE Trans. Neural Netw., 3 (6): 889–898, 1992.
- 10 S. Haykin Neural Networks: A Comprehensive Foundation, New York: Macmillan, 1994.
- 11 J. Zhang et al. Wavelet neural networks for function learning, IEEE Trans. Signal Process., 43 (6): 1485–1497, 1995.
- 12 B. Bakshi G. Stephanopoulos Wave-Net: A multiresolution, hierarchical neural network with localized learning, AIChE J., 39 (1): 57–81, 1993.
- 13 J. Park I. Sandberg Universal approximation using radial-basis-function networks, Neural Comp., 3 (2): 246–257, 1991.
- 14 T. Chen H. Chen Approximation capability to functions of several variables, nonlinear functionals, and operators by radial basis function neural networks, IEEE Trans. Neural Netw., 6 (4): 904–910, 1995.
- 15 J. Moody C. Darken Fast learning in networks of locally-tuned processing units, Neural Comput., 1 (2): 281–294, 1989.
- 16
C. Bishop
Improving the generalization properties of radial basis function neural networks,
Neural Comput.,
3 (4):
579–588,
1991.
10.1162/neco.1991.3.4.579 Google Scholar
- 17 B. Whitehead T. Choate Cooperative-competitive genetic evolution of radial basis function centers and widths for time series prediction, IEEE Trans. Neural Netw., 7 (4): 869–880, 1996.
- 18 S. Chen C. Cowan P. Grant Orthogonal least squares learning algorithm for radial basis function networks, IEEE Trans. Neural Netw., 2 (2): 302–309, 1991.
- 19 W. Ahmed Fast orthogonal search for training radial basis function neural networks, Master's thesis, Univ. of Maine, 1995.
- 20 J. Koh M. Suk S. Bhandarkar A multilayer self-organizing feature map for range image segmentation, Neural Netw., 8 (1): 67, 86, 1995.
Wiley Encyclopedia of Electrical and Electronics Engineering
Browse other articles of this reference work:
