Advanced Signal Processing Handbook: Theory and by Stergios Stergiopoulos

By Stergios Stergiopoulos

Advances in electronic sign processing algorithms and machine expertise have mixed to supply real-time platforms with features a ways past these of simply few years in the past. Nonlinear, adaptive equipment for sign processing have emerged to supply higher array achieve functionality, in spite of the fact that, they lack the robustness of traditional algorithms. The problem is still to boost an idea that exploits some great benefits of both-a scheme that integrates those equipment in functional, real-time systems.

The complicated sign Processing instruction manual is helping you meet that problem. past providing a great creation to the foundations and purposes of complex sign processing, it develops a frequent 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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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)

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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.

Stearns, Adaptive Signal Processing, Prentice-Hall, Englewood Cliffs, NJ, 1985. 4. A. A. Winder, Sonar system technology, IEEE Trans. Sonic Ultrasonics, SU-22(5), 291–332, 1975. 5. B. V. , Prentice-Hall, Englewood Cliffs, NJ, 1978. 6. J. Scudder, Introduction to computer aided tomography, Proc. IEEE, 66(6), 628–637, 1978. 7. C. Kak and M. Slaney, Principles of Computerized Tomography Imaging, IEEE Press, New York, 1992. 8. D. C. Kak, Ultrasonic Diffraction Imaging, TR-EE 82–80, Department of Electrical Engineering, Purdue University, West Lafayette, IN, August 1982.

Logistic function). 8 shows examples of these two forms of activation functions. • Shuffle the training examples after the presentation of each epoch; an epoch involves the presentation of the entire set of training examples to the network.

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