Comparison between traditional neural networks and radial basis function networks

Proceedings - ISIE 2011: 2011 IEEE International Symposium on Industrial Electronics

Volumn , Issue , 2011, Pages 1194-1199

  Xie, Tiantian ^a   Yu, Hao ^a   Wilamowski, Bogdan ^a  

^a AUBURN UNIVERSITY   (United States)

Author keywords

neural networks; radial basis function networks

Indexed keywords

COMPARISON RESULT; NETWORK MODELS; RADIAL BASIS FUNCTIONS; UNIVERSAL APPROXIMATORS;

INDUSTRIAL ELECTRONICS; NETWORK ARCHITECTURE; NEURAL NETWORKS;

RADIAL BASIS FUNCTION NETWORKS;

EID: 80052861320     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISIE.2011.5984328     Document Type: Conference Paper

References (24)

1. D. E. Rumelhart, G. E Hinton and R. J. Williams, "Learning Representations by Back-Propagating Errors," Nature, vol. 323, pp. 533-536, 1986.
2. J. Moody and C. J. Darken, "Fast Learning in Networks of Locally-Tuned Processing Units," Neural Computation, vol. 1, no. 2, pp. 281-294, 1989.
3. R. Hecht-Nielsen, "Counterpropagation Networks," Appl. Opt. 26(23):4979-4984, 1987.
4. A. G. Ivakhnenko and J. A. Mueller, "Self-Organizing of Nets of Active Neurons," System Analysis Modeling Simulation, vol. 20, pp. 93-106, 1995.
5. K. Derr and M. Manic, "Wireless based object tracking based on neural networks", ICIEA 2008, 3rd IEEE Conference on Industrial Electronics and Applications, Singapore, June 3-5, pp.308-313, 2008.
6. Y. J. Lee, J. Yoon, "Nonlinear Image Upsampling Method Based on Radial Basis Function Interpolation," IEEE Trans. on Image Processing, vol. 19, issue 10, pp. 2682-2692, 2010.
7. F. Moreno, J. Alarcón, et al., "Reconfigurable Hardware Architecture of a Shape Recognition System Based on Specialized Tiny Neural Networks With Online Training," IEEE Trans. on Industrial Electronics, vol. 56, no. 8, pp. 3253-3263, 2009.
8. O. Linda and M. Manic, "Online Spatio-Temporal Risk Assessment for Intelligent Transportation Systems." IEEE Trans. On Intelligent Transportation Systems, vol. 12, no. 1, pp. 194-200, 2011.
9. S. Huang and K. K. Tan, "Fault Detection and Diagnosis Based on Modeling and Estimation Methods," IEEE Trans. on Neural Networks, vol. 20, issue 5, pp. 872-881, Apr. 2009.
10. B. M. Wilamowski, N. J. Cotton, O. Kaynak, G. Dundar, "Computing Gradient Vector and Jacobian Matrix in Arbitrarily Connected Neural Networks," IEEE Trans. on Industrial Electronics, vol. 55, no. 10, pp. 3784-3790, Oct. 2008.
11. B. M. Wilamowski, R. C. Jaeger, "Implementation of RBF Type Networks by MLP Networks," IEEE International Conference on Neural Networks, Washington DC, June 3-6, 1996, pp. 1670-1675.
12. M. T. Hagan, M. B. Menhaj, "Training Feedforward Networks with the Marquardt Algorithm," IEEE Trans. on Neural Networks, vol. 5, no. 6, pp. 989-993, Nov. 1994.
13. B. M. Wilamowski and H. Yu, "Improved Computation for Levenberg Marquardt Training," IEEE Trans. on Neural Networks, vol. 21, no. 6, pp. 930-937, June 2010.
14. B. M. Wilamowski and H. Yu, "Neural Network Learning Without Backpropagation," IEEE Trans. on Neural Networks, vol. 21, no.11, pp. 1793-1803, Nov. 2010.
15. B. M. Wilamowski, "Modified EBP Algorithm with Instant Training of the Hidden Layer," Proceedings of Industrial Electronic Conference (IECON'97), New Orleans, November 9-14, 1997, pp. 1097-1101.
16. N. B. Karayiannis, "Reformulated Radial Basis Neural Networks Trained by Gradient Descent," IEEE Trans. Neural Networks, vol. 10, issue 3, pp. 657-671, Aug. 2002.
17. D. Simon, "Training Radial Basis Neural Networks with the Extended Kalman Filter," Neurocomputing, vol. 48, pp. 455-475, 2002.
18. B. A. Whitehead and T. D. Choate, "Cooperative-Competitive Genetic Evolution of Radial Basis Function Centers and Widths for Time Series Prediction," IEEE Trans. on Neural Networks, vol. 7, no. 4, pp. 869-880, July, 1996.
19. H. Yu, T. T. Xie, B. M. Wilamowski and J. Hewlett, "Fast and Efficient Second Order Method for Training Radial Basis Function Networks," IEEE Trans. on Neural Networks. (submitted)
20. H. Yu and B. M. Wilamowski, "Fast and efficient and training of neural networks," in Proc. 3rd IEEE Human System Interaction Conf. HSI 2010, Rzeszow, Poland, May 13-15, 2010, pp. 175-181.
21. H. Yu and B. M. Wilamowski, "Efficient and Reliable Training of Neural Networks," in Proc. 2nd IEEE Human System Interaction Conf. HSI 2009, Catania, Italy, May 21-23, 2009, pp. 109-115.
22. A. Malinowski and H. Yu, "Comparison of Embedded System Design for Industrial Applications," IEEE Trans. on Industrial Informactics. (accepted for publication)
23. B. M. Wilamowski, "Neural Network Architectures and Learning Algorithms: How Not to Be Frustrated with Neural Networks," IEEE Industrial Electronics Magazine, vol. 3, no. 4, pp. 56-63, Dec. 2009.
24. H. Yu and B. M. Wilamowski, "C++ Implementation of Neural Networks Trainer," 13-th International Conference on Intelligent Engineering Systems, INES09, Barbados, April 16-18, 2009.