By Stergios Stergiopoulos
Advances in electronic sign processing algorithms and laptop know-how have mixed to supply real-time structures with features 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, besides the fact that, they lack the robustness of traditional algorithms. The problem is still to enhance an idea that exploits some great benefits of both-a scheme that integrates those equipment in sensible, real-time systems.
The complicated sign Processing guide is helping you meet that problem. past supplying an exceptional advent to the rules and functions of complex sign processing, it develops a established processing constitution that takes benefit of 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
The mean-square value of the difference between the desired response and the transversal filter output). 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.
An adaptive filtering algorithm is said to be numerically robust when it is insensitive to variations in the word length used in its digital implementation. These factors, in their own ways, also enter into the design of nonlinear adaptive filters, except for the fact that we now no longer have a well-defined frame of reference in the form of a Wiener filter. Rather, we speak of a nonlinear filtering algorithm that may converge to a local minimum or, hopefully, a global minimum on the error-performance surface.
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