Efficient Time-Frequency Localization of a Signal

A new representation of the Fourier transform in terms of time and scale localization is discussed that uses a newly coined A-wavelet transform (Grigoryan 2005). The A-wavelet transform uses cosine- and sine-wavelet type functions, which employ, respectively, cosine and sine signals of length 2π. Fo...

Full description

Saved in:
Bibliographic Details
Main Author: Satish Chand
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:International Journal of Digital Multimedia Broadcasting
Online Access:http://dx.doi.org/10.1155/2014/529852
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832565231251881984
author Satish Chand
author_facet Satish Chand
author_sort Satish Chand
collection DOAJ
description A new representation of the Fourier transform in terms of time and scale localization is discussed that uses a newly coined A-wavelet transform (Grigoryan 2005). The A-wavelet transform uses cosine- and sine-wavelet type functions, which employ, respectively, cosine and sine signals of length 2π. For a given frequency ω, the cosine- and sine-wavelet type functions are evaluated at time points separated by 2π/ω on the time-axis. This is a two-parameter representation of a signal in terms of time and scale (frequency), and can find out frequency contents present in the signal at any time point using less computation. In this paper, we extend this work to provide further signal information in a better way and name it as A*-wavelet transform. In our proposed work, we use cosine and sine signals defined over the time intervals, each of length 2πm/(2nω), m≤2n, m and n are nonnegative integers, to develop cosine- and sine-type wavelets. Using smaller time intervals provides sharper frequency localization in the time-frequency plane as the frequency is inversely proportional to the time. It further reduces the computation for evaluating the Fourier transform at a given frequency. The A-wavelet transform can be derived as a special case of the A*-wavelet transform.
format Article
id doaj-art-4ef9e23bef544edbac13622c635920fa
institution Kabale University
issn 1687-7578
1687-7586
language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series International Journal of Digital Multimedia Broadcasting
spelling doaj-art-4ef9e23bef544edbac13622c635920fa2025-02-03T01:08:50ZengWileyInternational Journal of Digital Multimedia Broadcasting1687-75781687-75862014-01-01201410.1155/2014/529852529852Efficient Time-Frequency Localization of a SignalSatish Chand0Division of Computer Engineering, Netaji Subhas Institute of Technology, Sector-3, Dwarka, New Delhi 110 078, IndiaA new representation of the Fourier transform in terms of time and scale localization is discussed that uses a newly coined A-wavelet transform (Grigoryan 2005). The A-wavelet transform uses cosine- and sine-wavelet type functions, which employ, respectively, cosine and sine signals of length 2π. For a given frequency ω, the cosine- and sine-wavelet type functions are evaluated at time points separated by 2π/ω on the time-axis. This is a two-parameter representation of a signal in terms of time and scale (frequency), and can find out frequency contents present in the signal at any time point using less computation. In this paper, we extend this work to provide further signal information in a better way and name it as A*-wavelet transform. In our proposed work, we use cosine and sine signals defined over the time intervals, each of length 2πm/(2nω), m≤2n, m and n are nonnegative integers, to develop cosine- and sine-type wavelets. Using smaller time intervals provides sharper frequency localization in the time-frequency plane as the frequency is inversely proportional to the time. It further reduces the computation for evaluating the Fourier transform at a given frequency. The A-wavelet transform can be derived as a special case of the A*-wavelet transform.http://dx.doi.org/10.1155/2014/529852
spellingShingle Satish Chand
Efficient Time-Frequency Localization of a Signal
International Journal of Digital Multimedia Broadcasting
title Efficient Time-Frequency Localization of a Signal
title_full Efficient Time-Frequency Localization of a Signal
title_fullStr Efficient Time-Frequency Localization of a Signal
title_full_unstemmed Efficient Time-Frequency Localization of a Signal
title_short Efficient Time-Frequency Localization of a Signal
title_sort efficient time frequency localization of a signal
url http://dx.doi.org/10.1155/2014/529852
work_keys_str_mv AT satishchand efficienttimefrequencylocalizationofasignal