NDT.net - December 2002, Vol. 7 No.12

Nonlinear Dynamic Image Reconstruction for X-Ray Process Tomography

G.-R.Tillack, U.A. Samadurau
(Federal Institute for Materials Research and Testing (BAM),
Unter den Eichen 87, 12205 Berlin, Germany)
(Gerd-Ruediger.Tillack@bam.de)
V. M. Artemiev and A. O. Naumov
(Institute of Applied Physics, Akademicheskaya str. 16, 220072,
Minsk, Belarus) (artemiev@iaph.bas-net.by)
Paper presented at the 8th ECNDT, Barcelona, June 2002

Abstract

1. Problem formulation

2. Model equations

3. Statistical linearization approach

4. Example

5. Conclusion

References

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  2. V.M. Artemiev, A.O. Naumov and G.-R. Tillack, “Statistical Estimation theory Approach for the Dynamic Image Reconstruction”, 2nd World Congress on Industrial Process Tomography, Hannover, Germany, 2001, pp. 772–779
  3. V.M. Artemiev, A.O. Naumov and G.-R. Tillack, “Recursive Tomographic Image Reconstruction Using a Kalman Filter Approach in the Time Domain”, J.Phys.D: Appl.Phys, 34, 2001, pp 2073–2083
  4. A.H. Jazwinski, Stochastic Process and Filtering Theory, Academic Press, 1998 M.S. Jarlikov, M.A. Mironov, Markov Theory for Statistical Estimation of Random Processes (in Russian), Moscow, Radio i sviaz, 1993
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  6. M. Vauhkonen, P.A. Karjalainen and J.P. Kaipio, “A Kalman filter approach to track fast impedance changes in electrical impedance tomograpy”, IEEE Trans. Biomed. Eng., vol. 45, 1998, pp. 486–493
  7. I.E. Kazakov, “Nonlinear System Statistical Estimation Approach” (in Russian), Trans. Military Aircraft Engeneering Academy, vol. 394, 1954
  8. R.C. Booton, “Nonlinear control systems with random inputs”, Trans.IRE, Prof.group on circuit theory, Vol. PGIT-1, 1954, pp 9–18

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