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:
- Agilent Technologies
This text is a primer for those who are unfamiliar with the advantages of analysis in the frequency and modal domains and Dynamic Signal Analyzers. The authors avoid the use of rigorous mathematics and instead depend on heuristic arguments.
by Javier Prieto Tejedor (ed.) - InTech
This book takes a look at both theoretical foundations and practical implementations of Bayesian inference. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics.
by Salih Mohammed Salih (ed.) - InTech
The book covers fast hybrid recursive FT based on Jacket matrix, acquisition algorithm for global navigation system, determining the sensitivity of output parameters based on FFT, convergence of integrals based on Riemann-Lebesgue Lemma function, ...
by Julius O. Smith III - W3K Publishing
An introduction to digital filters, it covers mathematical theory, useful examples, audio applications, and some software starting points and Matlab programming examples. The theory treats concepts in digital filter analysis and linear systems theory.