首页> 外文会议>IEEE International Symposium on Circuits and Systems;ISCAS 2009 >Significant improvements in translating the Parks-McClellan Algorithm from its FORTRAN code to its corresponding MATLAB code
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Significant improvements in translating the Parks-McClellan Algorithm from its FORTRAN code to its corresponding MATLAB code

机译:将Parks-McClellan算法从其FORTRAN代码转换为相应的MATLAB代码方面的重大改进

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This article presents a highly optimized translation of the core discrete Remez multiple exchange (RME) part of the Parks-McClellan (PM) algorithm from its original FORTRAN code to its MATLAB counterpart. The optimization reduces the CPU execution time and code complexity. For achieving these goals, first, according to a thorough study of the existing FORTRAN code of the PM algorithm, the search in the core part for the ldquorealrdquo extremal points of the weighted error function, which is generated based on the ldquotrialrdquo extremal points, is compressed into only two compact basic search techniques. Secondly, vectors and matrices are used whenever possible due to many fast built-in operations in the MATLAB. Several examples are included to illustrate the superiority of the proposed MATLAB version of the PM algorithm over the existing function firpm, which is mostly based on a direct translation of the original FORTRAN code.
机译:本文介绍了Parks-McClellan(PM)算法的核心离散Remez多交换(RME)部分从其原始FORTRAN代码到其MATLAB副本的高度优化转换。优化减少了CPU执行时间和代码复杂度。为了实现这些目标,首先,根据对PM算法的现有FORTRAN代码的透彻研究,在核心部分中搜索基于ldquotrialrdquo极值点生成的加权误差函数的ldquorealrdquo极值点。压缩为仅两种紧凑的基本搜索技术。其次,由于MATLAB中许多快速的内置操作,因此尽可能使用向量和矩阵。包括几个示例,以说明提出的PM算法的MATLAB版本优于现有函数firpm的优势,后者主要基于原始FORTRAN代码的直接转换。

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