%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