A.H. Hadian-Rasanan
Shahid Beheshti University
5 Papers
17 Citations
A.H. Hadian-Rasanan is an academic researcher from Shahid Beheshti University. The author has contributed to research in topics: Nonlinear system & Numerical analysis. The author has an hindex of 2, co-authored 5 publications.
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Papers
An efficient space-splitting method for simulating brain neurons by neuronal synchronization to control epileptic activity
M. M. Moayeri,A.H. Hadian-Rasanan,Sobhan Latifi,Kourosh Parand,Kourosh Parand,Jamal Amani Rad +5 more
TL;DR: In this study, the generalized Lagrange Jacobi Gauss–Lobatto collocation method combined with Trotter operator splitting technique is employed, which allows us to decouple the nonlinear partial differential equations of neural network models into independent linear algebraic equations of very small dimensions.
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A development of Lagrange interpolation, Part I: Theory
TL;DR: The theorem of the derivative operational matrices of the classical Lagrange polynomials for the DLFs is developed and it is shown that the relation of $\textbf{D}^{(m)}=(\textbf(1)})^{m}$ for theDLFs is not established and is developable.
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A comparison between pre-Newton and post-Newton approaches for solving a physical singular second-order boundary problem in the semi-infinite interval
TL;DR: Two numerical approaches based on the Newton iteration method with spectral algorithms are introduced to solve the Thomas-Fermi equation, which is a nonlinear singular ordinary differential equation with boundary condition in infinite.
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MCILS: Monte-Carlo Interpolation Least-Square Algorithm for Approximation of Edge-Reliability Polynomial
A.H. Hadian-Rasanan,Dara Rahmati,Saeid Gorgin,Jamal Amani Rad +3 more
- 01 Oct 2019
TL;DR: A novel algorithm based on a hybrid Monte-Carlo, interpolation and least-square methods to approximate the reliability of a network is presented.
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A single layer fractional orthogonal neural network for solving various types of Lane-Emden equation
TL;DR: An artificial neural network framework is provided to approximate the solution of different types of Lane–Emden equation such as fractional order or system of Lane-Emden equations.