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Download Advances in Electronics and Electron Physics, Vol. 87 by Peter W. Hawkes (Ed.) PDF

By Peter W. Hawkes (Ed.)

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19. Darling, A. M. (1984). D. thesis, University of London. Darling, A. , Hall, T. , and Fiddy, M . A. (1983). “Stable, noniterative, object reconstruction from incomplete data using a priori data,” J . O . S . 73, 1466-1469. Donoho, D. , and Johnstone, I. M. (1989). “Projection-based approximation and a duality with kernel methods,” Annuls of’ Statistics 17(1), 58- 106. , and Malsburg, C. v. , eds. (1987). Neural Computers, NATO AS1 Series F, Vol. 41, Springer Verlag, Berlin. , and Stojancic, M.

And Trutzer, V. (1989). “Computationally feasible high-resolution minimumdistance procedures which extend the maximum-entropy method,” Inverse Problems 5, 749-766. Jones, L. , and Trutzer, V. (1990). “On extending the orthogonality property of minimum norm solutions in Hilbert space to general methods for linear inverse problems,” Inverse problems 6, 379-388. , and Gualtieri, J. A. (1992). “Solving inversion problems with neural networks,” Proc. IJCNN ’92, Baltimore, Vol. 111, p. 955. , New Jersey.

It is useful in the context of the pseudo-inverse content addressable memory, however, since it can more precisely discriminate between similar images in recall. An approach of greater generality to the image restoration problem allows one to incorporate more detailed information on the known or desired characteristics of the object o r image; for example, to predispose the reconstruction to a particular shape, or to control its behavior in the neighborhood of the prescribed boundaries. More specifically, this information can be introduced via weighting functions in the inner products associated with the Hilbert spaces of object and image.

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