Using Polynomial Regression in Designing the Time Filters for the Leapfrog Time-Stepping Scheme
Daniel Yazgi, Ali R. Mohebalhojeh, Sarmad Ghader
Abstract
Daniel Yazgi, Ali R. Mohebalhojeh, Sarmad Ghader
Abstract
Abstract A general framework is presented based on the least squares polynomial regression to design time filters for the leapfrog time-stepping scheme with required amplitude and phase properties. The well-known Robert–Asselin filter and its modification, the Robert–Asselin–Williams filter, are obtained using the zeroth-degree and first-degree polynomial regression, respectively. It is shown that using the second-degree polynomial regression, one can achieve seventh-order amplitude accuracy with only four time levels. In addition, the designed filter exhibits promising results when used with a semi-implicit time-stepping scheme.
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Abstract A general framework is presented based on the least squares polynomial regression to design time filters for the leapfrog time-stepping scheme with required amplitude and phase properties. The well-known Robert–Asselin filter and its modification, the Robert–Asselin–Williams filter, are obtained using the zeroth-degree and first-degree polynomial regression, respectively. It is shown that using the second-degree polynomial regression, one can achieve seventh-order amplitude accuracy with only four time levels. In addition, the designed filter exhibits promising results when used with a semi-implicit time-stepping scheme.
Key concepts: Polynomial regression, Polynomial, Degree (music), Regression, Filter (signal processing), Amplitude, Scheme (mathematics), Degree of a polynomial