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Seafloor Parameter Estimation: Approximating the Inverse Map Through RBF Networks

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Part of the book series: Modern Approaches in Geophysics ((MAGE,volume 12))

Abstract

A method for estimating the seafloor geoacoustic parameters from the measured acoustic field in the water is proposed. In particular, we impose to the inverse function the structure of a Radial Basis Function (RBF) expansion, and identify its coefficients using a set of computer generated input-output pairs. Among the advantages of the method are the robustness to noise in the data and the ability to compute the solution in real time. Succesfully estimated results are presented, with an accuracy that depends on their influence on the acoustic field.

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References

  1. Caiti, A., G. Magenes, T. Parisini, R. Simpson, (1994), “Smooth aprroximation by RBFs: three case studies”, J. Appl. Science and comp., vol. 1, n. 1, pp., 88–111.

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  2. Chen, S., C.F.N. Cowan, P.M. Grant, (1991), “Orthogonal least-squares algorithm for RBF networks”, IEEE Trans. Neural Networks, vol. 2, n. 2, pp. 302–309.

    Article  Google Scholar 

  3. Collins, M.D., W.A. Kuperman, H. Schmidt, (1992), “Non-linear inversion for ocean bottom properties”, J. Acoust. Soc. Am., vol. 92, n.5, pp. 2770–2783.

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  4. Hovem, J.M., À. Kristensen, (1992), “Reflection loss at a bottom with a fluid sediment layer over a hard solid halfspace”, J. Acoust. Soc. Am., vol. 92, n. 1, pp. 335–340.

    Article  Google Scholar 

  5. Poggio, T., F. Girosi, (1990), “Networks for approximation and learning”, Proc. IEEE, vol. 78, n. 9, pp. 1481–1497.

    Article  Google Scholar 

  6. Schmidt, H., (1988), “SAFARI User’s guide”, Report SR-113, SACLANTCEN, La Spezia, Italy.

    Google Scholar 

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© 1995 Springer Science+Business Media Dordrecht

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Caiti, A., Parisini, T., Zoppoli, R. (1995). Seafloor Parameter Estimation: Approximating the Inverse Map Through RBF Networks. In: Diachok, O., Caiti, A., Gerstoft, P., Schmidt, H. (eds) Full Field Inversion Methods in Ocean and Seismo-Acoustics. Modern Approaches in Geophysics, vol 12. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8476-0_29

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  • DOI: https://doi.org/10.1007/978-94-015-8476-0_29

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-4545-4

  • Online ISBN: 978-94-015-8476-0

  • eBook Packages: Springer Book Archive

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