Backpropagation method with type-2 fuzzy weight adjustment for neural network learning

2012 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2012

Volumn , Issue , 2012, Pages

  Gaxiola, Fernando ^a   Melin, Patricia ^a   Valdez, Fevrier ^a  

^a TIJUANA INSTITUTE OF TECHNOLOGY   (Mexico)

Author keywords

Backpropagation Algorithm; Neural Networks; Type 2 fuzzy system; Type 2 Fuzzy Weights

Indexed keywords

ENSEMBLE NEURAL NETWORK; FUZZY WEIGHT; LEARNING METHODS; MATHEMATICAL ANALYSIS; NEURAL NETWORK LEARNING; TIME SERIES PREDICTION; TYPE-2 FUZZY SYSTEMS;

BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; DATA PROCESSING; LEARNING SYSTEMS;

NEURAL NETWORKS;

EID: 84867716737     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NAFIPS.2012.6291056     Document Type: Conference Paper

References (33)

1. M. Cazorla and F. Escolano, "Two Bayesian Methods for Junction Detection", IEEE transaction on Image Processing, vol. 12, Issue 3, pp. 317-327, 2003.
2. G. Martinez, P. Melin, D. Bravo, F. Gonzalez and M. Gonzalez, "Modular Neural Networks and Fuzzy Sugeno Integral for Face and Fingerprint Recognition", Advances in Soft computing, vol .34, pp. 603-618, 2006.
3. O. De Wilde, "The Magnitude of the Diagonal Elements in Neural Networks", Neural Networks, vol. 10 (3), pp. 499-504, 1997.
4. P.A. Salazar, P. Melin and O. Castillo, "A New Biometric Recognition Technique Based on Hand Geometry and Voice Using Neural Networks and Fuzzy Logic", Soft Computing for Hybrid Intelligent Systems, pp. 171-186, 2008.
5. V.V. Phansalkar and P.S. Sastry, "Analysis of the Back-Propagation Algorithm with Momentum", IEEE Transactions on Neural Networks, vol. 5 (3). pp. 505-506, 1994.
6. T.G. Barbounis and J.B. Theocharis, "Locally Recurrent Neural Networks for Wind Speed Prediction using Spatial Correlation", Information Sciences, vol. 177 (24), pp. 5775-5797, 2007.
7. T. Gedeon, "Additive Neural Networks and Periodic Patterns", Neural Networks, vol. 12 (4-5), pp. 617-626, 1999.
8. M. Meltser, M. Shoham and L. Manevitz, "Approximating Functions by Neural Networks: A Constructive Solution in the Uniform Norm", Neural Networks, vol. 9 (6), pp. 965-978, 1996.
9. D. Yeung, P. Chan and W. Ng, "Radial Basis Function Network Learning using Localized Generalization Error Bound", Information Sciences, vol. 179 (19), pp. 3199-3217, 2009.
10. D. Casasent and S. Natarajan, "A Classifier Neural Net with Complex-Valued Weights and Square-Law Nonlinearities", Neural Networks, vol. 8 (6), pp. 989-998, 1995.
11. S. Draghici, "On the Capabilities of Neural Networks using Limited Precision Weights", Neural Networks, vol. 15 (3), pp. 395-414, 2002.
12. R.S. Neville and S. Eldridge, "Transformations of Sigma-Pi Nets: Obtaining Reflected Functions by Reflecting Weight Matrices", Neural Networks, vol. 15 (3), pp. 375-393, 2002.
13. J. Yam and T. Chow, "A Weight Initialization Method for Improving Training Speed in Feedforward Neural Network", Neurocomputing, vol. 30 (1-4), pp. 219-232, 2000.
14. M.T. Hagan, H.B. Demuth and M.H. Beale, "Neural Network Design", PWS Publishing, Boston, pp. 736, 1996.
15. R. Fletcher and C.M. Reeves, "Function Minimization by Conjugate Gradients", Computer Journal, vol. 7, pp. 149-154, 1964.
16. M . J . D Powell, "Restart Procedures for the Conjugate Gradient Method", Mathematical Programming, vol. 12, pp. 241-254, 1977.
17. E.M.L. Beale, "A Derivation of Conjugate Gradients", FA Lootsma ed., Numerical methods for nonlinear optimization, Academic Press, London, pp. 39-43, 1972.
18. M.F. Moller, "A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning", Neural Networks, vol. 6, pp. 525-533, 1993.
19. S. Kamarthi and S. Pittner, "Accelerating Neural Network Training using Weight Extrapolations", Neural Networks, vol. 12 (9), pp. 1285-1299, 1999.
20. H. Ishibuchi, K. Morioka and H. Tanaka, "A Fuzzy Neural Network with Trapezoid Fuzzy Weights, Fuzzy Systems", IEEE World Congress on Computational Intelligence, vol. 1, pp. 228-233, 1994.
21. H. . Ishibuchi, H. Tanaka and H. Okada, "Fuzzy Neural Networks with Fuzzy Weights and Fuzzy Biases", Neural Networks, IEEE International Conference on, vol. 3, pp. 1650-165, 1993.
22. T . Feuring, "Learning in Fuzzy Neural Networks", Neural Networks, IEEE International Conference on, vol. 2, pp. 1061-1066, 1996.
23. J. Castro, O. Castillo, P. Melin and A. Rodríguez-Díaz, "A Hybrid Learning Algorithm for a Class of Interval Type-2 Fuzzy Neural Networks", Information Sciences, vol. 179 (13), pp. 2175-2193, 2009.
24. J. Castro, O. Castillo, P. Melin, O. Mendoza and A. Rodríguez- Díaz, "An Interval Type-2 Fuzzy Neural Network for Chaotic Time Series Prediction with Cross-Validation and Akaike Test". Soft Computing for Intelligent Control and Mobile Robotics, pp. 269-285, 2011.
25. N. Karnik and J. Mendel, "Applications of Type-2 Fuzzy Logic Systems to Forecasting of Time-Series", Information Sciences, vol 120 (1-4). pp. 89-111, 1999.
26. R. Abiyev, "A Type-2 Fuzzy Wavelet Neural Network for Time Series Prediction", Lecture Notes in Computer Science, vol. 6098, pp. 518-527, 2010.
27. M.D. Monirul Islam and K. Murase, "A New Algorithm to Design Compact Two-Hidden-Layer Artificial Neural Networks", Neural Networks, vol. 14 (9), pp. 1265-1278, 2001.
28. J. S. R. Jang, C.T Sun and E. Mizutani, "Neuro-Fuzzy and Soft Computing: a Computational Approach to Learning and Machine Intelligence", Ed. Prentice Hall, pp. 614, 1997.
29. R. Haupt and S. Haupt, "Practical Genetic Algorithms", Ed. John Wiley and Sons, Inc., Hoboken, New Jersey, pp. 272, 2004.
30. O. Castillo and P. Melin, "A review on the design and optimization of interval type-2 fuzzy controllers". Applied Soft Computing, vol. 12 (4), pp. 1267-1278, 2012.
31. P. Melin, "Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition", Springer, pp. 1-204, 2012.
32. H. Hagras, "Type-2 Fuzzy Logic Controllers: A Way Forward for Fuzzy Systems in Real World Environments", IEEE World Congress on Computational Intelligence, pp. 181-200, 2008.
33. R. Sepúlveda, O. Castillo, P. Melin and O. Montiel, "An Efficient Computational Method to Implement Type-2 Fuzzy Logic in Control Applications". Analysis and Design of Intelligent Systems using Soft Computing Techniques, pp. 45-52, 2007.