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Biosignal and Biomedical Image Processing phần 3

Tham khảo tài liệu 'biosignal and biomedical image processing phần 3', kỹ thuật - công nghệ, kĩ thuật viễn thông phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 62 Chapter 3 Figure 3.1 Upper plot Segment of an EEG signal from the PhysioNet data bank Golberger et al. and the resultant power spectrum lower plot . The accurate determination of the waveform s spectrum requires that the signal be periodic or of finite length and noise-free. The problem is that in many biological applications the waveform of interest is either infinite or of sufficient length that only a portion of it is available for analysis. Moreover biosignals are often corrupted by substantial amounts of noise or artifact. If only a portion of the actual signal can be analyzed and or if the waveform contains noise along with the signal then all spectral analysis techniques must necessarily be approximate they are estimates of the true spectrum. The various spectral analysis approaches attempt to improve the estimation accuracy of specific spectral features. Intelligent application of spectral analysis techniques requires an understanding of what spectral features are likely to be of interest and which methods Copyright Marcel Dekker Inc. All rights reserved. Marcel Dekker Inc. 270 Madison Avenue New York New York 10016 TLFeBOOK Spectral Analysis Classical Methods 63 provide the most accurate determination of those features. Two spectral features of potential interest are the overall shape of the spectrum termed the spectral estimate and or local features of the spectrum sometimes referred to as parametric estimates. For example signal detection finding a narrowband signal in broadband noise would require a good estimate of local features. Unfortunately techniques that provide good spectral estimation are poor local estimators and vice versa. Figure 3.2A shows the spectral estimate obtained by applying the traditional Fourier transform to a waveform consisting of a 100 Hz sine wave buried in white noise. The SNR is minus 14 db that is the signal amplitude is 1 5 of the noise. Note that the 100 Hz sin wave is readily identified as a peak in the spectrum at .