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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by M. Stiber, B.Z. Stiber, E.C. Larson - University of Washington Bothell
The specific topics we will cover include: physical properties of the source information, devices for information capture, digitization, compression, digital signal representation, digital signal processing and network communication.
by Victor M. Moreno, Alberto Pigazo - INTECH
An overview of recent developments in Kalman filter theory and their applications in engineering and scientific fields. The book covers recent advances in Kalman filtering theory and applications in electrical engineering and other areas.
by R. J. Elliott, L. Aggoun, J. B. Moore - Springer
The aim of this book is to present graduate students with a thorough survey of reference probability models and their applications to optimal estimation and control. Readers are assumed to have basic grounding in probability and systems theory.
by Brad Osgood - Stanford University
This text is appropriate for science and engineering students. Topics include: Periodicity and Fourier series; The Fourier transform and its basic properties; Convolution and its applications; Distributions and their Fourier transforms; etc.