Inverse Nodal Problem for Sturm- Liouville Boundary Value Problem
Inverse nodal problems has been studied for Sturm-Liouville equations with point δ coaction. First, the eigenvalues of the problem are obtained. Then, the solution of the inverse problem is given by obtaining potential function and the parameters in the boundary conditions with the help of a dense set of nodal points.
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Spatial operator approach to flexible multibody system dynamics and control [PDF]
The inverse and forward dynamics problems for flexible multibody systems were solved using the techniques of spatially recursive Kalman filtering and smoothing.
Rodriguez, G.
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SPECTRAL PROPERTIES AND INVERSE NODAL PROBLEMS FOR SINGULAR DIFFUSION EQUATION
In this study, some properties for the pencils of singular Sturm-Liouville operators are investigated. Firstly, the behaviors of eigenvalues were learned, then the solutions of the inverse problem were given to determine the potential function and parameters of the boundary condition with the help of a dense set of nodal points and lastly we obtain a ...
Rauf AMİROV, Sevim DURAK
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Inverse nodal problem for p-Laplacian energy-dependent Sturm-Liouville equation [PDF]
Hikmet Koyunbakan
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Inverse nodal problems for Dirac operators and their numerical approximations
Fei Song +2 more
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Replication challenges in linking personality to resting-state functional connectomics. [PDF]
Jajcay N +7 more
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Time-space multiscale model for viscoelastic construction materials using the initial stress method. [PDF]
Wang X +5 more
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Inverse nodal problem for p-Laplacian differential operators
Bu tezde, p-Laplacian diferensiyel operatörleri çalışıldı. Tez beş temel kısımdan oluşmaktadır. Birinci bölümde, ters spektral teori ve p-Laplacian diferensiyel operatörlerinin tarihçesi verildi. Daha sonra, ikinci bölümde tez ile ilgili temel tanım ve teoremler ile genelleştirlmiş trigonometrik fonksiyonların bazı özellikleri ifade edildi.
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NeuralMag: an open-source nodal finite-difference code for inverse micromagnetics. [PDF]
Abert C +13 more
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Unifying machine learning and interpolation theory via interpolating neural networks. [PDF]
Park C +11 more
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