Signal and noise: Towards a general theory of algorithms

被引：0

作者：

Trivedi, S ^{[1
]}

Jones, B ^{[1
]}

Iyengar, S ^{[1
]}

机构：

[1] LOUISIANA STATE UNIV,DEPT COMP SCI,BATON ROUGE,LA 70803

来源：

CYBERNETICA | 1997年 / 40卷 / 02期

关键词：

algorithm theory; signal; noise; extrapolation;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a generalization of iterative numerical algorithms. An algorithm is considered to be composed of principal parts. Time series are associated with the algorithm and each of its principal parts. Each time series breaks down into dynamic signal and noise components. The problem treated in this immediate work is to extract signal from noise in the components of slow moving algorithms; thereby rapidly obtaining a solution. A program has been written to do extraction for slow algorithms, and it is applied to the principal parts of a well known algorithm for a well known characteristic test problem. The framework presented is general for analyzing and improving iterative numerical algorithms.

引用

页码：151 / 164

页数：14