Biosignal and Biomedical Image Processing by John L. Semmlow

By John L. Semmlow

A textbook for a one-semester direction combining sign and picture processing for graduate and complicated undergraduate scholars in biomedical engineering. scholars are assumed to have a few wisdom of the MATLAB software program package deal.

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Note the high sampling frequency that is required for what is basically a relatively low frequency signal (the ECG). 17 Detailed frequency plot (on a log-log scale) of a 4-pole and 8-pole filter, both having a cutoff frequency of 100 Hz. an 8-pole filter, would be a better choice in this situation. 17 shows that the frequency response of an 8-pole filter with the same 100 Hz frequency provides the necessary attenuation at less than 200 Hz. Using this filter, the sampling frequency could be lowered to under 400 Hz.

Since most signal processing operations are implemented using digital electronics, functions are represented in discrete form as a sequence of numbers: x(n) = [x(1),x(2),x(3), . . ,x(N)] (5) Discrete data functions (waveforms or images) are usually obtained through analog-to-digital conversion or other data input, while analysis or modifying functions are generated within the computer or are part of the computer program. ) In some applications, it is advantageous to think of a function (of whatever type) not just as a sequence, or array, of numbers, but as a vector.

Multiplied) by the magnitude of the input at that point in time. * Shifting and multiplication is sometimes referred to as the lag product. For most systems, h(τ) is finite, so the limit of integration is finite. Moreover, a real system can only respond to past inputs, so h(τ) must be 0 for τ < 0 (negative τ implies future times in Eq. (14), although for computer-based operations, where future data may be available in memory, τ can be negative. For discrete signals, the integration becomes a summation and the convolution equation becomes: N y(n) = ∑ h(n − k) x(k) or....

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