The First Order Rogue Waves Via Solutions 10 The Parameters Are The

The First Order Rogue Waves Via Solutions 10 The Parameters Are The We investigate a discrete ablowitz–ladik equation with variable coefficients, which models the modulated waves in an electrical lattice. employing the similarity transformation and kadomtsev. Further, the first order rogue wave solutions are given by a taylor expansion of the breather solutions. in particular, the explicit formula of the rogue wave has several parameters, which is more general than earlier reported results and thus provides a systematic way to tune experimentally the rogue waves by choosing different values for them.

The First Order Rogue Waves Via Solutions 10 The Parameters Are The We create first , second , and third order rogue wave solutions via direct computation for various values of center controlled parameters and suitable choices of different constants in the said. We employ symbolic computation directly to create the rogue waves using the center controlled parameters $$\beta $$ and $$\gamma $$ . we create first , second , and third order rogue wave solutions via direct computation for various values of center controlled parameters and suitable choices of different constants in the said equation. Specifically, first and second order rogue wave solutions for the focusing nls equation and three deformed rogue wave solutions for the variable coefficient nls equation are solved using physics informed memory networks (pimns). the effects of optimization algorithm, network structure, and mesh size on the solution accuracy are discussed. In particular, when we assume that the coefficient of the equation is θ = m x d t ⁠, some new wave structures are found based on parameter variations, such as the rotational separation of first order rogue waves, scale like structures generated by second order breathers, etc., which offer novel ideas for producing different signals via.

The First Order Rogue Waves Via Solutions 10 The Parameters Are The Specifically, first and second order rogue wave solutions for the focusing nls equation and three deformed rogue wave solutions for the variable coefficient nls equation are solved using physics informed memory networks (pimns). the effects of optimization algorithm, network structure, and mesh size on the solution accuracy are discussed. In particular, when we assume that the coefficient of the equation is θ = m x d t ⁠, some new wave structures are found based on parameter variations, such as the rotational separation of first order rogue waves, scale like structures generated by second order breathers, etc., which offer novel ideas for producing different signals via. 3.2.2. second order rogue wave. similar to the way of deriving data driven one soliton, two soliton and first order rogue wave solutions, we construct the dataset based on the mathematical expression of the exact second order rogue wave solution in ref. [55]. In the past few decades, the research of traveling wave solutions explored by researchers has gained considerable attention. it includes the solutions of non linear partial differential equations.

First Order Rogue Wave Solutions Given By 10 With Download 3.2.2. second order rogue wave. similar to the way of deriving data driven one soliton, two soliton and first order rogue wave solutions, we construct the dataset based on the mathematical expression of the exact second order rogue wave solution in ref. [55]. In the past few decades, the research of traveling wave solutions explored by researchers has gained considerable attention. it includes the solutions of non linear partial differential equations.