Modern Spectral Estimation PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Modern Spectral Estimation PDF full book. Access full book title Modern Spectral Estimation by Steven M. Kay. Download full books in PDF and EPUB format.
Author: Steven M. Kay
Publisher: Pearson Education India
ISBN: 9788131733561
Category : Estimation theory
Languages : en
Pages : 564
Get Book Here
Book Description
Author: Steven M. Kay
Publisher: Pearson Education India
ISBN: 9788131733561
Category : Estimation theory
Languages : en
Pages : 564
Get Book Here
Book Description
Author: Steven M. Kay
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 574
Get Book Here
Book Description
Author: Steven M. Kay
Publisher: Prentice-Hall PTR
ISBN: 9780130151599
Category : Education
Languages : en
Pages : 539
Get Book Here
Book Description
Author: Petre Stoica
Publisher: Pearson Education
ISBN:
Category : Mathematics
Languages : en
Pages : 358
Get Book Here
Book Description
This book presents an introduction to spectral analysis that is designed for either course use or self-study. Clear and concise in approach, it develops a firm understanding of tools and techniques as well as a solid background for performing research. Topics covered include nonparametric spectrum analysis (both periodogram-based approaches and filter- bank approaches), parametric spectral analysis using rational spectral models (AR, MA, and ARMA models), parametric method for line spectra, and spatial (array) signal processing. Analytical and Matlab-based computer exercises are included to develop both analytical skills and hands-on experience.
Author: Donald B. Percival
Publisher: Cambridge University Press
ISBN: 9780521435413
Category : Mathematics
Languages : en
Pages : 616
Get Book Here
Book Description
This book is an up-to-date introduction to univariate spectral analysis at the graduate level, which reflects a new scientific awareness of spectral complexity, as well as the widespread use of spectral analysis on digital computers with considerable computational power. The text provides theoretical and computational guidance on the available techniques, emphasizing those that work in practice. Spectral analysis finds extensive application in the analysis of data arising in many of the physical sciences, ranging from electrical engineering and physics to geophysics and oceanography. A valuable feature of the text is that many examples are given showing the application of spectral analysis to real data sets. Special emphasis is placed on the multitaper technique, because of its practical success in handling spectra with intricate structure, and its power to handle data with or without spectral lines. The text contains a large number of exercises, together with an extensive bibliography.
Author: S. Lawrence Marple, Jr.
Publisher: Courier Dover Publications
ISBN: 048678052X
Category : Technology & Engineering
Languages : en
Pages : 435
Get Book Here
Book Description
Digital Spectral Analysis offers a broad perspective of spectral estimation techniques and their implementation. Coverage includes spectral estimation of discrete-time or discrete-space sequences derived by sampling continuous-time or continuous-space signals. The treatment emphasizes the behavior of each spectral estimator for short data records and provides over 40 techniques described and available as implemented MATLAB functions. In addition to summarizing classical spectral estimation, this text provides theoretical background and review material in linear systems, Fourier transforms, matrix algebra, random processes, and statistics. Topics include Prony's method, parametric methods, the minimum variance method, eigenanalysis-based estimators, multichannel methods, and two-dimensional methods. Suitable for advanced undergraduates and graduate students of electrical engineering — and for scientific use in the signal processing application community outside of universities — the treatment's prerequisites include some knowledge of discrete-time linear system and transform theory, introductory probability and statistics, and linear algebra. 1987 edition.
Author: Mischa Schwartz
Publisher:
ISBN:
Category :
Languages : en
Pages : 396
Get Book Here
Book Description
Author: Burkhard Buttkus
Publisher: Springer Science & Business Media
ISBN: 364257016X
Category : Science
Languages : en
Pages : 665
Get Book Here
Book Description
This state-of-the-art survey serves as a complete overview of the subject. Besides the principles and theoretical foundations, emphasis is laid on practical applicability -- describing not only classical methods, but also modern developments and their applications. Students, researchers and practitioners, especially in the fields of data registration, treatment and evaluation, will find this a wealth of information.
Author: Ravindran Kannan
Publisher: Now Publishers Inc
ISBN: 1601982747
Category : Computers
Languages : en
Pages : 153
Get Book Here
Book Description
Spectral methods refer to the use of eigenvalues, eigenvectors, singular values and singular vectors. They are widely used in Engineering, Applied Mathematics and Statistics. More recently, spectral methods have found numerous applications in Computer Science to "discrete" as well as "continuous" problems. Spectral Algorithms describes modern applications of spectral methods, and novel algorithms for estimating spectral parameters. The first part of the book presents applications of spectral methods to problems from a variety of topics including combinatorial optimization, learning and clustering. The second part of the book is motivated by efficiency considerations. A feature of many modern applications is the massive amount of input data. While sophisticated algorithms for matrix computations have been developed over a century, a more recent development is algorithms based on "sampling on the fly" from massive matrices. Good estimates of singular values and low rank approximations of the whole matrix can be provably derived from a sample. The main emphasis in the second part of the book is to present these sampling methods with rigorous error bounds. It also presents recent extensions of spectral methods from matrices to tensors and their applications to some combinatorial optimization problems.
Author: Steven M. Kay
Publisher: Pearson Education
ISBN: 013280803X
Category : Technology & Engineering
Languages : en
Pages : 496
Get Book Here
Book Description
"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples."--Cover, volume 1.
