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Adaptive phase-singular-unit restoration with entire-spectrum-processing complex-valued neural networks in interferometric SAR

Adaptive phase-singular-unit restoration with entire-spectrum-processing complex-valued neural networks in interferometric SAR

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A singular-unit restoration filter based on complex-valued neural networks that deal with spatial spectrum in interferometric synthetic aperture radar is proposed. This filter utilises more neural generalisation ability than conventional methods. In experiments, it shows a higher accuracy as well as shorter processing time than conventional real-space filters and shorter learning time than previous spectral-domain learning filters.

References

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      • 1. Ghiglia, D., Pritt, M.: ‘Two-dimensional phase unwrapping: theory, algorithms, and softwareser. Wiley-Interscience publication (Wiley, New York, NY, USA, 1998).
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      • 10. Hirose, A.: ‘Applications of complex-valued neural networks to coherent optical computing using phase-sensitive detection scheme’, Inf. Sci. Appl., 1994, 2, pp. 103117.
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      • 11. Hirose, A.: ‘Complex-valued neural networks’ (Springer, Heidelberg, Berlin, New York, 2012, 2nd edn.).
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