In this paper an approach for decreasing the computational effort required for the split-step Fourier method SSFM is introduced. It is shown that using the sparsity property of the simulated signals, the compressive sampling algorithm can be used as a very efficient tool for the split-step spectral simulations of various phenomena which can be modeled by using differential equations. The proposed method depends on the idea of using a smaller number of spectral components compared to the classical split-step Fourier method with a high number of components. After performing the time integration with a smaller number of spectral components and using the compressive sampling technique with l1 minimization, it is shown that the sparse signal can be reconstructed with a significantly better efficiency compared to the classical split-step Fourier method. Proposed method can be named as compressive split-step Fourier method CSSFM . For testing of the proposed method the Nonlinear Schr¨odinger Equation and its one-soliton and two-soliton solutions are considered.
Compressive sampling nonlinear Schr¨odinger equation sparse signals splitstep Fourier method
Primary Language | English |
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Journal Section | Research Article |
Authors | |
Publication Date | December 1, 2015 |
Published in Issue | Year 2015 Volume: 5 Issue: 2 |