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Time-Frequency and Wavelet Analysis

  • Suresh R. Devasahayam
Chapter
  • 1.1k Downloads
Part of the Topics in Biomedical Engineering International Book Series book series (TOBE)

Abstract

We have already noted some of the limitations of Fourier decomposition. The assumption of periodicity in the calculation of the DFT is one main limitation. Another more subtle limitation is the unavoidable compromise between time resolution and frequency resolution. This is due to the fact that the DFT is computed on a block of data. This fixes the time window or resolution as ΔT r=N/F s, where N is the block size and F S is the sampling rate. It also fixes the frequency resolution as ΔF r=F s/N. The product of the time resolution and frequency resolution, ΔT r•ΔF r is constant, which means that improvement in time resolution can be obtained only at the expense of frequency resolution and vice versa.

Keywords

Wavelet Analysis Wavelet Coefficient Slow Component Finite Impulse Response Frequency Resolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    M. Akay, Detection and Estimation Methods of Biomedical Signals, Academic Press, 1996.Google Scholar
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    M. Akay (ed.), Time frequency and Wavelets in Biomedical Signal Processing IEEE Press, 1998.zbMATHGoogle Scholar
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    M.S. Kumaran, and S.R. Devasahayam, Wavelet Decomposition of Myoelectric Reflexes-Time Feature Extraction of the Blink Reflex and its use in Clinical Diagnosis. Proceedings of the 5 th Biennial Conference on Signal Processing and Comm., BSc, Bangalore, 67–72 (July 1999).Google Scholar

Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Suresh R. Devasahayam
    • 1
  1. 1.School of Biomedical EngineeringIndian Institute of TechnologyBombayIndia

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