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Adaptive LMS power series analytical solution for differential algebraic equations

机译:微分代数方程的自适应LMS幂级数解析解

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Differential Algebraic Equations (DAEs) are essential in the analysis of many engineering, physical, chemical and mathematical systems. Numerical methods are popular to solve highly nonlinear and even linear DAEs. On the other hand, analytical solutions for DAEs are very limited. This work presents an efficient analytical solution for DAEs based on power series regressions. The coefficients of the estimated power series solution are adaptively computed employing the computationally simple signed least mean squares adaptive algorithm. The DAEs are assumed to be on the general implicit canonical form. The proposed adaptive power series method can solve linear and nonlinear DAEs systems. The efficient and accurate solutions provided by the technique proposed are illustrated through simulated examples. It is shown that the performance of the technique proposed outperforms existing conventional and modern methods.
机译:在许多工程,物理,化学和数学系统的分析中,微分代数方程(DAE)是必不可少的。数值方法是解决高度非线性甚至线性DAE的流行方法。另一方面,用于DAE的分析解决方案非常有限。这项工作提出了基于幂级数回归的DAE的有效分析解决方案。估计的幂级数解的系数是使用计算简单的有符号最小均方自适应算法自适应计算的。假定DAE采用通用的隐式规范形式。所提出的自适应幂级数方法可以解决线性和非线性DAEs系统。通过仿真示例说明了所提出的技术所提供的有效而准确的解决方案。结果表明,所提出的技术性能优于现有的传统方法和现代方法。

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