e-books in Signal Processing category
by Javier Prieto Tejedor (ed.) - InTech , 2017
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 G. Nikolic, M. Cakic, D. Cvetkovic (eds) - InTech , 2017
The book provides a review on recent advances in Fourier transforms as the most powerful analytical tool for applications in electronic and computer engineering, as well as spectral techniques with a wide range of nanotechnological applications.
by Vesa Valimaki - MDPI AG , 2017
Audio signal processing is a highly active research field where digital signal processing theory meets human sound perception and real-time programming requirements. It has a wide range of applications in computers, gaming, music technology, etc.
by Allen B. Downey - Green Tea Press , 2014
'Think DSP: Digital Signal Processing in Python' is an introduction to signal processing and system analysis using a computational approach. The premise of this book is that if you know how to program, you can use that skill to learn other things.
by Salih Mohammed Salih (ed.) - InTech , 2015
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 William A. Gardner - Prentice Hall , 1988
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.
by F.P.G. Marquez, N. Zaman (ed.) - InTech , 2013
Digital filters, together with signal processing, are being employed in the new technologies and information systems, and implemented in different areas and applications. This book presents advanced developments, covering different cases studies.
by Paolo Prandoni, Martin Vetterli - EFPL Press , 2008
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 Salih Mohammed Salih - InTech , 2012
This book focuses on the Fourier transform applications in signal processing techniques. Topics covered: DFT, FFT, OFDM, estimation techniques and the image processing techniques. Written for electrical engineers, communication engineers, etc.
by John Treichler - Connexions , 2009
This book examines how to convert a typical filter specification into a reasonably accurate estimate of the length of the impulse response. The text covers filter sizing, performance comparisons with other FIR design methods, etc.
by Michael Wakin - Connexions , 2009
This book reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, etc.
by Fausto Pedro García Marquez - InTech , 2011
Digital filters are the most versatile, practical and effective methods for extracting the information necessary from the signal. This book presents the most advanced digital filters including different case studies and the most relevant literature.
- Agilent Technologies , 2000
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 Sebastian Miron - InTech , 2010
The exponential development of computer power over the last few decades, transformed signal processing in an essential tool for a wide range of domains such as telecommunications. This book provides highlights of the current research in the area.
by William A. Gardner - McGraw-Hill , 1990
A first course on random processes for graduate engineering and science students, particularly those with an interest in the analysis and design of signals and systems. The book includes detailed coverage of minimum-mean-squared-error estimation.
by Carl W. Helstrom - Prentice Hall , 1994
This is an introduction to signal-detection theory, a subject fundamental to the design of detectors of weak signals in the presence of random noise, and to the design of optimal receivers of communication, radar, sonar and optical signals.
by Sophocles J. Orfanidis , 2007
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 Sophocles J. Orfanidis - Prentice Hall , 2009
An applications-oriented introduction to digital signal processing. The author covers all the basic DSP concepts, such as sampling, DFT/FFT algorithms, etc. The book emphasizes the algorithmic, computational, and programming aspects of DSP.
by Raghu Raj Bahadur, at al. - IMS , 2002
In this volume the author covered what should be standard topics in a course of parametric estimation: Bayes estimates, unbiased estimation, Fisher information, Cramer-Rao bounds, and the theory of maximum likelihood estimation.
by Vedran Kordic - InTech , 2010
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.
by J. H. Karl - Academic Press , 1989
The book comprises a one-semester or self-study course, filling the gap between several oversimplified introductions and more topically specialized or formal treatments. Karl's book wins notable points for its easy reading style.
by Brad Osgood - Stanford University , 2009
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 Julius O. Smith III - DSPRelated.com , 2007
This book was developed for a course entitled 'Signal Processing Methods in Musical Acoustics'. The text was created primarily as a research preparation and dissemination vehicle intended for graduate students in computer music and engineering.
by H. V. Poor, G. W. Wornell - Prentice-Hall, Inc. , 1998
A valuable reference both for signal processing specialists seeking to apply their expertise in the rapidly growing wireless communications field, and for communications specialists eager to exploit signal processing techniques.
by R. J. Elliott, L. Aggoun, J. B. Moore - Springer , 1995
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 B.D.O. Anderson, J.B. Moore - Prentice-Hall , 1979
This graduate-level text augments and extends studies of signal processing, particularly in regard to communication systems and digital filtering theory. Topics include filtering, linear systems, and estimation; the discrete-time Kalman filter; etc.
by Bruce Hajek - University of Illinois at Urbana-Champaign , 2009
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.
by E. A. Lee, P. Varaiya - Addison Wesley , 2002
An introduction to signals and systems for electrical engineering, computer engineering, and computer science students. The material motivates signals and systems through sound and images, as opposed to circuits. Calculus is the only prerequisite.
by John C. Nash - Marcel Dekker Inc , 1995
This book and software collection is intended to help scientists, engineers and statisticians in their work. We have collected various software tools for nonlinear parameter estimation, along with representative example problems.
by C. Sidney Burrus, at al. - Connexions , 2008
This book uses an index map, a polynomial decomposition, an operator factorization, and a conversion to a filter to develop a very general description of fast algorithms to calculate the discrete Fourier transform. Computer programs are provided.
by Victor M. Moreno, Alberto Pigazo - INTECH , 2009
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 Michele Basseville, Igor V. Nikiforov - Prentice-Hall , 1993
This book presents mathematical tools and techniques for solving change detection problems in wide domains like signal processing, controlled systems and monitoring. The book is intended for engineers and researchers involved in signal processing.
by G. Larry Bretthorst - Springer , 1988
This work is a research document on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis.
- Xilinx, Inc. , 2005
The book for DSP designers who want to tap the power of the Virtex-4 XtremeDSP Slice. It provides a description of the features of the slice as well as multiple examples that show you how to harness the power and flexibility of this IP block.
by Sergio Rui Silva - InTech , 2009
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 Zoran Milivojević - mikroElektronika , 2009
The book provides various theoretical and practical approaches to digital filter design. It covers design of both finite and infinite impulse response filters. It applies the most commonly used design methods giving the best solutions.
by Avinash C. Kak, Malcolm Slaney - IEEE Press , 1989
A comprehensive, tutorial-style introduction to the algorithms for reconstructing cross-sectional images from projection data and contains a complete overview of the engineering and signal processing algorithms necessary for tomographic imaging.
by P. Vaidyanathan - Morgan and Claypool Publishers , 2008
Linear prediction theory has had a profound impact in the field of digital signal processing. This book focuses on the theory of vector linear prediction and line spectral processes. There are several examples and computer-based demonstrations.
by Walt Kester - Newnes , 2002
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 Julius O. Smith III - W3K Publishing , 2007
Detailed mathematical derivation of DFT (Discrete Fourier Transform), with elementary applications to audio signal processing. Matlab programming examples are included. High-school math background is a prerequisite, including some calculus.
by Julius O. Smith III - W3K Publishing , 2007
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.
by Steven W. Smith - California technical Publishing , 1999
Digital Signal Processing is one of the most powerful technologies that will shape science and engineering in the twenty-first century. The book presents the fundamentals of DSP using examples from common science and engineering problems.
by Daniel N. Rockmore, Jr, Dennis M. Healy - Cambridge University Press , 2004
The book about the mathematical basis of signal processing and its many areas of application for graduate students. The text emphasizes current challenges, new techniques adapted to new technologies, and recent advances in algorithms and theory.
by R. M. Gray, L. D. Davisson - Cambridge University Press , 2005
The book covers basic probability, random objects, expectation, second order moment theory with examples of the random process models and their basic properties, specific applications for communication, estimation, detection, modulation.