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.
Home page url
Download or read it online for free here:
by Sophocles J. Orfanidis
In this edition the emphasis is on real-time adaptive signal processing, eigenvector methods of spectrum estimation, and parallel processor implementations of optimum filtering and prediction algorithms, and including several new developments.
by Walt Kester - Newnes
The book explains signal processing hardware. It covers sampled data systems, A-to-D and D-to-A converters for DSP applications, fast Fourier transforms, digital filters, DSP hardware, interfacing to DSP chips, hardware design techniques.
by Paolo Prandoni, Martin Vetterli - EFPL Press
The book is less focused on the mathematics and more on the concepts, allowing students to think about the subject at a higher conceptual level, thus building the foundations for more advanced topics and helping students solve real-world problems.
by Samuel Davey, et al. - Springer
This book demonstrates how nonlinear/non-Gaussian Bayesian time series estimation methods were used to produce a probability distribution of potential MH370 flight paths. The probability distribution was used to define the search zone in the Ocean.