Interpolating earth-science data using RBF networks and mixtures of experts

Advances in Neural Information Processing Systems

Volumn , Issue , 1997, Pages 988-994

  Wan, E ^a   Bone, D ^a  

^a CSIRO   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; MIXTURES; RADIAL BASIS FUNCTION NETWORKS;

COVARIATION; INPUT SPACE; INTERPOLATION METHOD; KRIGING; MIXTURE OF EXPERTS; MIXTURES OF EXPERTS; REAL-WORLD; SPATIAL DEPENDENCE;

INTERPOLATION;

EID: 80054740247     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. Cressie, N. A. (1993). Statistics for Spatial Data. Wiley, New York.
2. Jacobs, R. A., Jordan, M. I., Nowlan, S. J. & Hinton, G. E. (1991). Adaptive Mixtures of Local Experts. Neural Computation 3, pp. 79-87.
3. Jordan, M. I. & Jacobs, R. A. (1994). Hierarchical Mixtures of Experts and the EM Algorithm. Neural Computation 6, pp. 181-214.
4. Mac Kay, D. J. (1992). Bayesian Interpolation. Neural Computation 4, pp. 415-47.
5. Orr, M. J. (1995). Regularization in the Selection of Radial Basis Function Centers. Neural Computation 7, pp. 606-623.
6. Poggio, T. & Girosi, F. (1990). Networks for Approximation and Learning. In Proceedings of the IEEE7S, pp. 1481-1497.
7. Wan, E. & Bone, D. (1996). A Neural Network Approach to Covariation Model Fitting and the Interpolation of Sparse Earth-science Data. In Proceedings of the Seventh Australian Conference on Neural Networks, pp. 121-126.