Tham khảo tài liệu 'biosignal and biomedical image processing matlab-based applications muya phần 3', ngoại ngữ, anh văn thương mại phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 60 Chapter 2 Use a sampling rate of 500 Hz and set the damping factor Ỗ to and the frequency fn termed the undamped natural frequency to 10 Hz. The array should be the equivalent of at least seconds of data. Plot the impulse response to check its shape. Again convolve this impulse response with a 512-point noise array and construct and plot the autocorrelation function of this array. Save the outputs for use in a spectral analysis problem at the end of Chapter 3. See Problem 6 Chapter 3. 8. Construct 4 damped sinusoids similar to the signal y t in Problem 7. Use a damping factor of and generate two seconds of data assuming a sampling frequency of 500 Hz. Two of the 4 signals should have an fn of 10 Hz and the other two an fn of 20 Hz. The two signals at the same frequency should be 90 degrees out of phase replace the sin with a cos . Are any of these four signals orthogonal Copyright Marcel Dekker Inc. All rights reserved. Marcel Dekker Inc. 270 Madison Avenue New York New York 10016 TLFeBOOK 3 Spectral Analysis Classical Methods INTRODUCTION Sometimes the frequency content of the waveform provides more useful information than the time domain representation. Many biological signals demonstrate interesting or diagnostically useful properties when viewed in the so-called frequency domain. Examples of such signals include heart rate EMG EEG ECG eye movements and other motor responses acoustic heart sounds and stomach and intestinal sounds. In fact just about all biosignals have at one time or another been examined in the frequency domain. Figure shows the time response of an EEG signal and an estimate of spectral content using the classical Fourier transform method described later. Several peaks in the frequency plot can be seen indicating significant energy in the EEG at these frequencies. Determining the frequency content of a waveform is termed spectral analysis and the development of useful approaches for this frequency decomposition has a long .
