期刊文献+

改进的算术傅立叶变换(AFT)算法 被引量:5

Improved Arithmetic Fourier Transform Algorithms
在线阅读 下载PDF
导出
摘要 算术傅立叶变换 (AFT)是一种非常重要的傅立叶分析技术 .AFT的乘法量少 (仅为O(N) ) ,算法结构简单 ,非常适合VLSI设计 ,具有广泛的应用 .但AFT的加法量很大 ,为O(N2 ) ,因此减少AFT的加法运算量是很重要的工作 .本文通过分析AFT的采样特点 ,给出了奇函数和偶函数的AFT的改进算法 .然后在此基础上给出了一般函数的AFT的改进算法 .改进算法比原算法的加法运算量降低了一半 ,因此计算速度快了一倍 .本文改进的偶函数和奇函数的AFT算法还分别可以用来计算离散余弦变换 (DCT)和离散正弦变换 (DST) . The arithmetic Fourier transform (AFT) is a very important Fourier analysis technique. AFT needs only O (N) multiplications and has simple computational structure, so it is very suitable for VLSI design. It arises in many applications. But AFT needs many additions (O(N2)), so it is very important to reduce its number of additions. By analyzing sampling characteristics of AFT, this paper gives improved algorithms of AFT for odd and even functions, and based on these algorithms, gives an improved AFT algorithm for general functions. The improved algorithms reduce the number of additions of AFT algorithms to a half and increase the computational speeds to double. The improved AFT algorithms for even and odd functions can also be computing discrete cosine transform (DCT) and discrete sine transform (DST), respectively.
出处 《电子学报》 EI CAS CSCD 北大核心 2001年第3期329-331,共3页 Acta Electronica Sinica
基金 国家 8 63计划项目!(No .863 30 6 2D1 1 0 1 2 )
关键词 算术傅立叶变换 离散余弦变换 离散正弦变换 函数 Algorithms Cosine transforms Digital arithmetic Functions Number theory
  • 相关文献

参考文献5

二级参考文献10

共引文献31

同被引文献48

  • 1Bruns H.Grundlinien des Wissenschaftlichnen Rechnens[M].Leipzig,Personal Publication,1903.
  • 2Tufts D W,Sadasiv G.The arithmetic Fourier transform[J].IEEE ASSP Mag,1988,5(1):13-17.
  • 3Reed I S,Tufts D W,Xiao Yu,et al..Fourier analysis and signal processing by use of Mobius inversion formular[J].IEEE Trans.on Acoust,Speech,Signal Processing,1990,38(3):458-470.
  • 4Reed I S,Shih M T,Troung T K,et al..A VLSI architecture for simplified arithmetic Fourier transform algorithms[J].IEEE Trans.on Acoust,Speech,Signal Processing,1993,40(5):1122-1132.
  • 5Lovine F P,Tantaratanas S.Some alternate realizations of the arithmetic Fourier transform.[C].Proceedings of the Twenty-Seventh Annual Asilomar Conference on Signals,Systems,and Computers,Pacific Grove,California,1993:310-314.
  • 6Ge Xi-Jin,Chen Nan-Xian,Chen Zhao-Dou.Efficient algorithm for 2-D arithmetic Fourier transform[J].IEEE Trans.on Signal Processing,1997,45(8):2136-2140.
  • 7Wigley N Jullien.A sampling reduction for the arithmetic Fourier transform[C].Proc,32nd Midwest Symposium on Circuits and Systems,Champaign,IL,1990:841-844.
  • 8Knckaert L.A generalized Mobius transform,arithmetic Fourier transform,and primitive roots[J].IEEE Trans.on Signal Processing,1996,44(5):1307-1310.
  • 9Schiff J,Walker W.The arithmetic Fourier transform.Analysis,geometry and groups:A Riemann legacy volume,Hadronic Press Collect.Orig.Artic.,Palm Harbor,FL,Hadronic Press,1993:613-625.
  • 10Walker W.The arithmetic Fourier transform and real neural networks:summability by primes[J].J.Math.Anal.Appl.1995,190:211-219.

引证文献5

二级引证文献11

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部