By Stergios Stergiopoulos
Advances in electronic sign processing algorithms and machine know-how have mixed to provide real-time structures with functions 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, although, they lack the robustness of traditional algorithms. The problem continues to be to increase an idea that exploits the benefits of both-a scheme that integrates those tools in useful, real-time systems.
The complicated sign Processing instruction manual is helping you meet that problem. past providing an excellent creation to the foundations and functions of complex sign processing, it develops a commonly used 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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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)
Geosci. Remote Sensing, 32, 768–778, 1994. 38. J. , Wavelets and image fusion, Proc. 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.
In their own individual ways, the LMS and GAL algorithms are just two members of the stochastic gradient family of linear adaptive filters, although it must be said that the LMS algorithm is by far the most popular member of this family. 2 Least-Squares Estimation The second approach to the development of linear adaptive filtering algorithms is based on the method of least squares. According to this method, we minimize a cost function or index of performance that is defined as the sum of weighted error squares, where the error or residual is itself defined as the difference between some desired response and the actual filter output.
5 Real and Complex Forms of Adaptive Filters In the development of adaptive filtering algorithms, regardless of their origin, it is customary to assume that the input data are in baseband form. The term “baseband” is used to designate the band of frequencies representing the original (message) signal as generated by the source of information. In such applications as communications, radar, and sonar, the information-bearing signal component of the receiver input typically consists of a message signal modulated onto a carrier wave.
Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real Time Systems (Electrical Engineering & Applied Signal Processing Series) by Stergios Stergiopoulos