The estimation of low and high-pass active filter parameters with opposite charged system search algorithm
作者：
Highlights：
• CSS is a stable structure algorithm in the literature.
• The opposition-based learning structure is integrated into CSS.
• The parameter estimation of the AC filters is an important engineering problem.
• Parameter estimation of low and high pass filters was done with CSS and OCSS.
• The predictive filter parameters were successfully estimated.
摘要
•CSS is a stable structure algorithm in the literature.•The opposition-based learning structure is integrated into CSS.•The parameter estimation of the AC filters is an important engineering problem.•Parameter estimation of low and high pass filters was done with CSS and OCSS.•The predictive filter parameters were successfully estimated.
论文关键词：Charged system search algorithm (CSS),Opposite charged system search algorithm (OCSS),Sallen-Key topology Butterworth low and high-pass active filters,E24 standard series
论文评审过程：Received 14 March 2019, Revised 29 March 2020, Accepted 20 April 2020, Available online 27 April 2020, Version of Record 6 May 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113474
