Research Letters in Signal Processing
Volume 2008 (2008), Article ID 932068, 5 pages
doi:10.1155/2008/932068
Research Letter

An Adaptive Resolution Computationally Efficient Short-Time Fourier Transform

Saeed Mian Qaisar, Laurent Fesquet, and Marc Renaudin

TIMA, CNRS UMR 5159, 46 avenue Felix-Viallet, 38031 Grenoble Cedex, France

Received 31 January 2008; Accepted 22 April 2008

Academic Editor: Sos Agaian

Copyright © 2008 Saeed Mian Qaisar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The short-time Fourier transform (STFT) is a classical tool, used for characterizing the time varying signals. The limitation of the STFT is its fixed time-frequency resolution. Thus, an enhanced version of the STFT, which is based on the cross-level sampling, is devised. It can adapt the sampling frequency and the window function length by following the input signal local characteristics. Therefore, it provides an adaptive resolution time-frequency representation of the input signal. The computational complexity of the proposed STFT is deduced and compared to the classical one. The results show a significant gain of the computational efficiency and hence of the processing power.