Stabilized algorithms for ill-posed problems in signal processing

Author

Buyun, Zhang ; Dinghua, Xu ; Tangwei, Liu

Author_Institution

Dept. of Electron. Eng., Nanjing Univ. of Sci. & Technol., China

Volume

1

fYear

2001

fDate

2001

Firstpage

375

Abstract

In this paper we discuss two kinds of ill-posed problems in signal processing, that is, in detail, reconstructing compactly supported signals in the Fourier transform and solving the convolution equation with analytic kernel. Having analyzed the essential reason of ill-posedness for these problems, we present some stabilized algorithms, which cure the ill-posedness, to recover the approximate solution. Finally numerical experiments show the efficiency and fast convergence of these algorithms

Keywords

Fourier transforms; approximation theory; convolution; numerical stability; signal reconstruction; Fourier transform; analytic kernel; approximate solution; compactly supported signal; convergence; convolution equation; ill-posed problems; numerical simulation; signal processing; signal reconstruction; stabilized algorithms; Algorithm design and analysis; Convolution; Equations; Fourier transforms; Image reconstruction; Kernel; Mathematical model; Signal analysis; Signal processing; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on

Conference_Location

Beijing

Print_ISBN

0-7803-7010-4

Type

conf

DOI

10.1109/ICII.2001.982776

Filename

982776