By Stergios Stergiopoulos
Advances in electronic sign processing algorithms and machine expertise have mixed to supply real-time structures with functions a long way past these of simply few years in the past. Nonlinear, adaptive equipment for sign processing have emerged to supply higher array achieve functionality, besides the fact that, they lack the robustness of traditional algorithms. The problem continues to be to improve an idea that exploits the benefits of both-a scheme that integrates those equipment in useful, real-time systems.
The complicated sign Processing instruction manual is helping you meet that problem. past providing a superb creation to the foundations and purposes of complex sign processing, it develops a standard processing constitution that takes good thing about the similarities that exist between radar, sonar, and clinical imaging structures and integrates traditional and nonlinear processing schemes.
Read Online or Download Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real Time Systems (Electrical Engineering & Applied Signal Processing Series) PDF
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Extra info for Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real Time Systems (Electrical Engineering & Applied Signal Processing Series)
Furthermore, the presence of feedback introduces a new problem, namely, that of stability. , break into oscillation), unless special precaution is taken in the choice of feedback coefficients. By contrast, an FIR filter in inherently stable. This explains the reason for the popular use of FIR filters, in one form or another, as the structural basis for the design of linear adaptive filters. 4 Approaches to the Development of Linear Adaptive Filtering Algorithms There is no unique solution to the linear adaptive filtering problem.
The Wiener filter is inadequate for dealing with situations in which nonstationarity of the signal and/or noise is intrinsic to the problem. In such situations, the optimum filter has to assume a time-varying form. A highly successful solution to this more difficult problem is found in the Kalman filter, a powerful device with a wide variety of engineering applications. Linear filter theory, encompassing both Wiener and Kalman filters, has been developed fully in the literature for continuous-time as well as discrete-time signals.
To obtain the baseband representation of a narrowband signal, the signal is translated down in frequency in such a way that the effect of the carrier wave is completely removed, yet the information content of the message signal is fully preserved. In general, the baseband signal so obtained is complex. 6) where u1(n) is the in-phase (real) component, and uQ(n) is the quadrature (imaginary) component. 7) where |u(n)| is the magnitude, and φ(n) is the phase angle. 2 assume the use of complex signals.