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Biosignal and Biomedical Image Processing MATLAB-Based Applications Muya phần 7

Tham khảo tài liệu 'biosignal and biomedical image processing matlab-based applications muya phần 7', ngoại ngữ, anh văn thương mại phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 222 Chapter 8 Ox Plot frequency characteristics of unknown and identified process f 1 N fs N Construct freq. vector for plotting subplot 1 2 1 Plot unknown system freq. char. plot f 1 N 2 ps_unknown 1 N 2 k .labels table axis. subplot 1 2 2 Plot matching system freq. char. plot f 1 N 2 ps_match 1 N 2 k .labels table axis. The output plots from this example are shown in Figure 8.4. Note the close match in spectral characteristics between the unknown process and the matching output produced by the Wiener-Hopf algorithm. The transfer functions also closely match as seen by the similarity in impulse response coefficients h n unknown 0.5 0.75 1.2 h n match 0.503 0.757 1.216 . ADAPTIVE SIGNAL PROCESSING The area of adaptive signal processing is relatively new yet already has a rich history. As with optimal filtering only a brief example of the usefulness and broad applicability of adaptive filtering can be covered here. The FIR and IIR filters described in Chapter 4 were based on an a priori design criteria and were fixed throughout their application. Although the Wiener filter described above does not require prior knowledge of the input signal only the desired outcome it too is fixed for a given application. As with classical spectral analysis methods these filters cannot respond to changes that might occur during the course of the signal. Adaptive filters have the capability of modifying their properties based on selected features of signal being analyzed. A typical adaptive filter paradigm is shown in Figure 8.5. In this case the filter coefficients are modified by a feedback process designed to make the filter s output y n as close to some desired response d n as possible by reducing the error e n to a minimum. As with optimal filtering the nature of the desired response will depend on the specific problem involved and its formulation may be the most difficult part of the adaptive system specification Stearns and David 1996 . The inherent stability of FIR filters .