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Eid H. Doha

Researcher at Cairo University

Publications -  132
Citations -  4594

Eid H. Doha is an academic researcher from Cairo University. The author has contributed to research in topics: Jacobi polynomials & Spectral method. The author has an hindex of 36, co-authored 128 publications receiving 4023 citations. Previous affiliations of Eid H. Doha include King Abdulaziz University.

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A Chebyshev spectral method based on operational matrix for initial and boundary value problems of fractional order

TL;DR: The shifted Chebyshev operational matrix (COM) of fractional derivatives is derived and used together with spectral methods for solving FDEs and the proposed algorithms are applied to solve two types ofFDEs, linear and nonlinear, subject to initial or boundary conditions.
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A new jacobi operational matrix: an application for solving fractional differential equations

TL;DR: In this paper, the shifted Jacobi operational matrix (JOM) of fractional derivatives was derived and applied together with spectral tau method for numerical solution of general linear multi-term fractional differential equations (FDEs).
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Efficient Chebyshev spectral methods for solving multi-term fractional orders differential equations

TL;DR: A new formula expressing explicitly the derivatives of shifted Chebyshev polynomials of any degree and for any fractional-order in terms of shiftedChebyshevs themselves is state and prove.
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A spectral tau algorithm based on Jacobi operational matrix for numerical solution of time fractional diffusion-wave equations

TL;DR: An efficient and accurate spectral numerical method is presented for solving second-, fourth-order fractional diffusion-wave equations and fractional wave equations with damping based on Jacobi tau spectral procedure together with the Jacobi operational matrix for fractional integrals, described in the Riemann-Liouville sense.
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Efficient spectral-Galerkin algorithms for direct solution of fourth-order differential equations using Jacobi polynomials

TL;DR: Numerical results indicate that the direct solvers presented in this paper are significantly more accurate at large N values than that based on the Chebyshev- and Legendre-Galerkin methods.