Magnetotelluric inversion using regularized Hopfield neural networks

Geophysical Prospecting

Volumn 45, Issue 5, 1997, Pages 725-743

  Zhang, Yuanchou ^a   Paulson, K V ^b  

^a UNIVERSITY OF TORONTO   (Canada)

^b UNIVERSITY OF SASKATCHEWAN   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

INVERSE PROBLEMS; OPTIMIZATION; PARALLEL PROCESSING SYSTEMS; PROBLEM SOLVING;

HOPFIELD NEURAL NETWORK; MAGNETOTELLURIC INVERSION;

NEURAL NETWORKS;

HOPFIELD NETWORK; MAGNETOTELLURIC INVERSION; NEURAL NETWORK;

EID: 0031225042     PISSN: 00168025     EISSN: None     Source Type: Journal    
DOI: 10.1046/j.1365-2478.1997.660299.x     Document Type: Article

References (28)

1. Alspector J. 1989. Neural-style microsystems that learn. IEEE Communications Magazine 27 (11), 29-36.
2. Bostick F.X. 1977. A simple almost exact method of MT analysis. In: Workshop on Electrical Methods in Geothermal Exploration, pp. 1-14, University of Utah, Salt Lake City.
3. Constable S.C., Parker R.L. and Constable C.G. 1987. Occam's inversion: A practical algorithm for generating smooth models from electromagnetic sounding data. Geophysics 52, 289-300.
4. Culhane A.D., Peckerar M.C. and Marrian C.R. 1989. A neural net approach to discrete Hartley and Fourier transforms. IEEE Transactions on Circuits and Systems 36, 695-703.
5. deGroot-Hedlin C. and Constable S. 1993. Occam's inversion and the North American Central Plains electrical anomaly. Journal of Geomagnetism and Geoelectrics 45, 985-999.
6. Farhat N.H. and Bai B. 1989. Echo inversion and target shape estimation by neuromorphic processing. Neural Networks 2, 117-125.
7. Farhat N.H., Psaltis D., Prata A. and Paek E. 1985. Optical implementation of the Hopfield model. Applied Optics 24, 1469-1475.
8. Hopfield J.J. 1982. Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences, U.S.A. 79, 2554-2558.
9. Hopfield J.J. and Tank D.W. 1985. Neural computation of decisions in optimization problems. Biological Cybernetics 52, 141-152.
10. Ising E. 1925. Beitrag zur theorie des ferromagnetismus. Zeitschrift für Physik 31, 253-258.
11. Jiao J., Paulson K.V. and Zhang Y. 1994. Minimum cross-entropy inversion of magnetotelluric data in one and two dimensions. Program and Abstracts, Canadian Geophysical Union Meeting, Banff, 12, pp. 11-12.
12. Jones A.G. 1993. The COPROD2 data set: tectonic setting, recorded MT data, and comparison of models. Journal of Geomagnetism and Geoelectrics 45, 933-955.
13. Jones A.G. and Hutton R. 1979. A multistation magnetotelluric study in southern Scotland - II. Monte-Carlo inversion of the data and its geophysical and tectonic implications. Geophysical Journal of the Royal Astronomical Society 56, 351-368.
14. Jupp D.L.B. and Vozoff K. 1977. Two-dimensional magnetotelluric inversion. Geophysical Journal of the Royal Astronomical Society 50, 333-352.
15. Kulkarni A.D. 1991. Solving ill-posed problems with artificial neural networks. Neural Networks 4, 477-484.
16. Larsen J.C. 1981. A new technique for layered earth magnetotelluric inversion. Geophysics 46, 1247-1257.
17. Oldenburg D.W. 1979. One-dimensional inversion of natural source magnetotelluric observations. Geophysics 44, 1218-1244.
18. Sivilotti M.A., Mahowald M.A. and Mead C.A. 1987. Real-time visual computations using analog CMOS processing arrays. In: Advanced Research in VLSI: Proceedings of Stanford Conference (ed. P. Losleben), pp. 295-312. MIT Press.
19. Tank D.W. and Hopfield J.J. 1986. Simple neural optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit. IEEE Transactions on Circuits and Systems 33, 535-541.
20. Tikhonov A.N. and Arsenin V.Y. 1977. Solutions of Ill-Posed Problems. John Wiley & Sons, Inc.
21. Wang L.X. and Mendel J.M. 1992. Adaptive minimum prediction-error deconvolution and source wavelet estimation using Hopfield neural networks. Geophysics 57, 670-679.
22. Wannamaker P.E., Stodt J.A. and Rijon L. 1987. A stable finite element solution for two-dimensional magnetotelluric modelling. Geophysical Journal of the Royal Astronomical Society 88, 277-296.
23. Weidelt P. 1972. The inverse problem of geomagnetic induction. Zeitschrift für Geophysik 38, 257-289.
24. Yee E. and Paulson K.V. 1988a. Necessary and sufficient conditions for the existence of a solution to the one-dimensional magnetotelluric inverse problem. Geophysical Journal of the Royal Astronomical Society 93, 279-293.
25. Yee E. and Paulson K.V. 1988b. Properties of the c-response function for conductivity distributions of class. Geophysical Journal of the Royal Astronomical Society 93, 265-278.
26. Yee E. and Paulson K.V. 1988c. Concerning dispersion relations for the magnetotelluric impedance tensor. Geophysical Journal of the Royal Astronomical Society 95, 549-559.
27. Young J.F. 1971. Information Theory. Wiley Interscience.
28. Zhang Y. 1996. Applications of wavelet transforms, neural networks and migration to magnetotelluric data. Ph.D. thesis, University of Saskatchewan.