%0 Journal Article
	%A Saeed Mian Qaisar and  Laurent Fesquet and  Marc Renaudin
	%D 2008
	%J International Journal of Electronics and Communication Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 17, 2008
	%T Computationally Efficient Adaptive Rate Sampling and Adaptive Resolution Analysis
	%U https://publications.waset.org/pdf/12095
	%V 17
	%X Mostly the real life signals are time varying in nature. For proper characterization of such signals, time-frequency representation is required. The STFT (short-time Fourier transform) is a classical tool used for this purpose. 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 variations. Therefore, it provides an adaptive resolution time-frequency representation of the input. 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. The processing error of the proposed technique is also discussed.

	%P 979 - 984