By Stergios Stergiopoulos
Advances in electronic sign processing algorithms and machine expertise have mixed to provide real-time platforms with features some distance past these of simply few years in the past. Nonlinear, adaptive equipment for sign processing have emerged to supply larger array achieve functionality, in spite of the fact that, they lack the robustness of traditional algorithms. The problem is still to enhance an idea that exploits the benefits of both-a scheme that integrates those equipment in useful, real-time systems.
The complex sign Processing guide is helping you meet that problem. past supplying a good creation to the rules and purposes of complicated sign processing, it develops a wide-spread processing constitution that takes good thing about the similarities that exist between radar, sonar, and scientific imaging structures and integrates traditional and nonlinear processing schemes
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Additional info for Advanced signal processing handbook : theory and implementation for radar, sonar, and medical imaging real time systems
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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).
SPIE, 2569, 208–219, 1995. 39. D. Kundur and D. Hatzinakos, Blind image deconvolution, Signal Processing Magazine, 13, 43–64, May 1996. 40. , Chelmsford, MA, 1998. 41. S. Stergiopoulos, R. Alterson, D. Havelock, and J. Grodski, Acoustic Tomography Methods for 3D Imaging of Shallow Buried Objects, 139th Meeting of the Acoustical Society of America, Atlanta, GA, May 2000. 1 The Filtering Problem The term “filter” is often used to describe a device in the form of a piece of physical hardware or software that is applied to a set of noisy data in order to extract information about a prescribed quantity of interest.