By Stergios Stergiopoulos
Advances in electronic sign processing algorithms and desktop know-how have mixed to provide real-time platforms with services a ways past these of simply few years in the past. Nonlinear, adaptive equipment for sign processing have emerged to supply greater array achieve functionality, even though, they lack the robustness of traditional algorithms. The problem continues to be to boost an idea that exploits some great 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 supplying a great advent to the rules and purposes of complicated sign processing, it develops a customary processing constitution that takes good thing about the similarities that exist between radar, sonar, and scientific imaging platforms and integrates traditional and nonlinear processing schemes.
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Additional resources for Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real Time Systems
4) where u(n) is the lattice predictor input at time n. 4 and given the set of reflection coefficients κ1, κ2, …, κM – 1, we may determine the final pair of outputs fM – 1(n) and bM – 1(n) by moving through the lattice predictor, stage by stage. For a correlated input sequence u(n), u(n – 1), …, u(n – M + 1) drawn from a stationary process, the backward prediction errors b0, b1(n), …, bM – 1(n) form a sequence of uncorrelated random variables. Moreover, there is a one-to-one correspondence between these two sequences of random variables in the sense that if we are given one of them, we may uniquely determine the other and vice versa.
This cost function is precisely a second-order function of the tap weights in the transversal filter. , punch bowl) with a uniquely defined bottom or minimum point. As mentioned previously, we refer to this paraboloid as the error-performance surface; the tap weights corresponding to the minimum point of the surface define the optimum Wiener solution. To develop a recursive algorithm for updating the tap weights of the adaptive transversal filter, we proceed in two stages. , the matrix equation defining the optimum Wiener solution) through the use of the method of steepest descent, a well-known technique in * In the general definition of a function, we speak of a transformation from a vector space into the space of real (or complex) scalars (Luenberger, 1969; Dorny, 1975).
14. J. R. D. F. King, and Y. Kim, Correction of computed tomography motion artifacts using pixel-specific back-projection, IEEE Trans. Medical Imaging, 15(3), 333–342, 1996. 15. S. Stergiopoulos, Implementation of adaptive and synthetic-aperture processing schemes in integrated active-passive sonar systems, Proc. IEEE, 86(2), 358–396, 1998. 16. D. Stansfield, Underwater Electroacoustic Transducers, Bath University Press and Institute of Acoustics, 1990. 17. M. T. M. M. , Chapman & Hall, New York, 1988.
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