A flexible and approximate computing approach for time-frequency distributions

Author

Le, Thuyen ; Glesner, Manfred

Author_Institution

Inst. of Microelectron. Syst., Darmstadt Univ. of Technol., Germany

Volume

48

Issue

4

fYear

2000

fDate

4/1/2000 12:00:00 AM

Firstpage

1193

Lastpage

1196

Abstract

Eigen-decomposition of the kernel allows fast computation of time-frequency distributions. This paper proposes a scheme which exploits further approximation by adapting dynamically the accuracy of spectrograms to the eigenvalue magnitudes. The approach employs the wavelet transform followed by block-recursive Fourier transform and a compensation network. It provides a set of parameters for the users to trade accuracy against computational complexity so that the implementation can be tailored to a specific application

Keywords

approximation theory; computational complexity; discrete Fourier transforms; eigenvalues and eigenfunctions; filtering theory; spectral analysis; time-frequency analysis; wavelet transforms; approximation; block-recursive Fourier transform; compensation network; computational complexity; eigen-decomposition; eigenvalue magnitudes; fast computation; kernel; spectrograms; time-frequency distributions; wavelet transform; Computational complexity; Discrete Fourier transforms; Distributed computing; Eigenvalues and eigenfunctions; Fourier transforms; Kernel; Spectral analysis; Spectrogram; Time frequency analysis; Wavelet transforms;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.827553

Filename

827553