A Robust and Scalable Implementation of the Parks-McClellan Algorithm for Designing FIR Filters

作者：Filip Silviu Ioan^*

来源：ACM Transactions on Mathematical Software, 2016, 43(1): 7.

DOI：10.1145/2904902

• Algorithms
• Performance
• Barycentric interpolation
• Chebyshev approximation
• colleague matrix
• FIR filters
• minimax approximation
• Lebesgue constant

With a long history dating back to the beginning of the 1970s, the Parks-McClellan algorithm is probably the most well known approach for designing finite impulse response filters. Despite being a standard routine in many signal processing packages, it is possible to find practical design specifications where existing codes fail to work. Our goal is twofold. We first examine and present solutions for the practical difficulties related to weighted minimax polynomial approximation problems onmulti-interval domains (i.e., the general setting under which the Parks-McClellan algorithm operates). Using these ideas, we then describe a robust implementation of this algorithm. It routinely outperforms existing minimax filter design routines.

• 出版日期2016-8