An Introduction to Statistical Signal Processing
by R. M. Gray, L. D. Davisson
Publisher: Cambridge University Press 2005
Number of pages: 478
This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book.
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Simulation and 3D reconstruction of side-looking sonar images, synthetic aperture techniques, ensemble averaging and resolution enhancement of digital radar and sonar signals, multi-sonar integration and the advent of sensor intelligence, and more.
by Jeff Fessler - University of Michigan
Course objectives: 1. to teach students the concepts of discrete-time signals, including mathematical representations; 2. to teach students the concepts of linear time-invariant discrete-time systems; 3. to introduce the concepts of filter design.
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by Bruce Hajek - University of Illinois at Urbana-Champaign
These notes were written for a graduate course on random processes. Students are assumed to have had a previous course in probability, some familiarity with real analysis and linear algebra, and some familiarity with complex analysis.