Statistical Spectral Analysis: A Non-Probabilistic Theory
by William A. Gardner
Publisher: Prentice Hall 1988
Number of pages: 591
This book is intended to serve as both a graduate-level textbook and a technical reference. The focus is on fundamental concepts, analytical techniques, and basic empirical methods. The only prerequisite is an introductory course on Fourier analysis.
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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 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 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.
by Vedran Kordic - InTech
The Kalman filter has been successfully employed in diverse knowledge areas over the last 50 years. The aim of this book is to provide an overview of recent developments in Kalman filter theory and their applications in engineering and science.