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Journal of Mathematical Analysis and Applications
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Remarks on a New Inverse Nodal Problem

Remarks on a new inverse nodal problem
Authors: Cheng, Yan-Hsiou; Law, C.K.; Tsay, Jhishen;

Remarks on a New Inverse Nodal Problem

Abstract

The authors weaken the conditions and simplify the proof of a theorem of \textit{X. F. Yang} [A new inverse nodal problem, J. Differ. Equations (to appear)]. It is known that the usual nodal inverse problem developed by \textit{J. R. McLaughlin} [J. Differ. Equations, 73, No. 2, 354-362 (1988; Zbl 0652.34029)] is overdetermined. That makes possible to reduce the data sufficient to determine the potential of the Sturm-Liouville equation and the boundary conditions. The authors use the results of \textit{F. Gesztesy} and \textit{B. Simon} [Inverse spectral analysis with partial information on the potential, II, The case of discrete spectrum, Trans. Am. Math. Soc. 352, No. 6, 2765-2787 (2000)].

Related Organizations
Keywords

Sturm-Liouville theory, nodal length, Borg's theorem, Applied Mathematics, Inverse problems involving ordinary differential equations, nodal inverse problem, Sturm-Liouville problem, Analysis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
73
Top 10%
Top 10%
Average
hybrid