Statistical Digital Signal Processing and Modeling

Statistical Digital Signal Processing and Modeling
Author :
Publisher : John Wiley & Sons
Total Pages : 629
Release :
ISBN-10 : 9780471594314
ISBN-13 : 0471594318
Rating : 4/5 (14 Downloads)

Book Synopsis Statistical Digital Signal Processing and Modeling by : Monson H. Hayes

Download or read book Statistical Digital Signal Processing and Modeling written by Monson H. Hayes and published by John Wiley & Sons. This book was released on 1996-04-19 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main thrust is to provide students with a solid understanding of a number of important and related advanced topics in digital signal processing such as Wiener filters, power spectrum estimation, signal modeling and adaptive filtering. Scores of worked examples illustrate fine points, compare techniques and algorithms and facilitate comprehension of fundamental concepts. Also features an abundance of interesting and challenging problems at the end of every chapter.

Statistical Digital Signal Processing and Modeling

Statistical Digital Signal Processing and Modeling
Author :
Publisher : John Wiley & Sons
Total Pages : 628
Release :
ISBN-10 : 8126516100
ISBN-13 : 9788126516100
Rating : 4/5 (00 Downloads)

Book Synopsis Statistical Digital Signal Processing and Modeling by : Monson H. Hayes

Download or read book Statistical Digital Signal Processing and Modeling written by Monson H. Hayes and published by John Wiley & Sons. This book was released on 2009-08 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main thrust is to provide students with a solid understanding of a number of important and related advanced topics in digital signal processing such as Wiener filters, power spectrum estimation, signal modeling and adaptive filtering. Scores of worked examples illustrate fine points, compare techniques and algorithms and facilitate comprehension of fundamental concepts. The book also features an abundance of interesting and challenging problems at the end of every chapter.· Background· Discrete-Time Random Processes· Signal Modeling· The Levinson Recursion· Lattice Filters· Wiener Filtering· Spectrum Estimation· Adaptive Filtering

Digital Signal Processing and Statistical Classification

Digital Signal Processing and Statistical Classification
Author :
Publisher : Artech House
Total Pages : 522
Release :
ISBN-10 : 1580531350
ISBN-13 : 9781580531351
Rating : 4/5 (50 Downloads)

Book Synopsis Digital Signal Processing and Statistical Classification by : George J. Miao

Download or read book Digital Signal Processing and Statistical Classification written by George J. Miao and published by Artech House. This book was released on 2002 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to introduce and integrate advanced digital signal processing (DSP) and classification together, and the only volume to introduce state-of-the-art transforms including DFT, FFT, DCT, DHT, PCT, CDT, and ODT together for DSP and communication applications. You get step-by-step guidance in discrete-time domain signal processing and frequency domain signal analysis; digital filter design and adaptive filtering; multirate digital processing; and statistical signal classification. It also helps you overcome problems associated with multirate A/D and D/A converters.

Digital and Statistical Signal Processing

Digital and Statistical Signal Processing
Author :
Publisher : CRC Press
Total Pages : 505
Release :
ISBN-10 : 9780429017575
ISBN-13 : 042901757X
Rating : 4/5 (75 Downloads)

Book Synopsis Digital and Statistical Signal Processing by : Anastasia Veloni

Download or read book Digital and Statistical Signal Processing written by Anastasia Veloni and published by CRC Press. This book was released on 2018-10-03 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, many aspects of electrical and electronic engineering are essentially applications of DSP. This is due to the focus on processing information in the form of digital signals, using certain DSP hardware designed to execute software. Fundamental topics in digital signal processing are introduced with theory, analytical tables, and applications with simulation tools. The book provides a collection of solved problems on digital signal processing and statistical signal processing. The solutions are based directly on the math-formulas given in extensive tables throughout the book, so the reader can solve practical problems on signal processing quickly and efficiently. FEATURES Explains how applications of DSP can be implemented in certain programming environments designed for real time systems, ex. biomedical signal analysis and medical image processing. Pairs theory with basic concepts and supporting analytical tables. Includes an extensive collection of solved problems throughout the text. Fosters the ability to solve practical problems on signal processing without focusing on extended theory. Covers the modeling process and addresses broader fundamental issues.

Statistical and Adaptive Signal Processing

Statistical and Adaptive Signal Processing
Author :
Publisher : Artech House Publishers
Total Pages : 824
Release :
ISBN-10 : STANFORD:36105114109536
ISBN-13 :
Rating : 4/5 (36 Downloads)

Book Synopsis Statistical and Adaptive Signal Processing by : Dimitris G. Manolakis

Download or read book Statistical and Adaptive Signal Processing written by Dimitris G. Manolakis and published by Artech House Publishers. This book was released on 2005 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt: This authoritative volume on statistical and adaptive signal processing offers you a unified, comprehensive and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing. Packed with over 3,000 equations and more than 300 illustrations, this unique resource provides you with balanced coverage of implementation issues, applications, and theory, making it a smart choice for professional engineers and students alike.

Fundamentals of Statistical Signal Processing

Fundamentals of Statistical Signal Processing
Author :
Publisher : Pearson Education
Total Pages : 496
Release :
ISBN-10 : 9780132808033
ISBN-13 : 013280803X
Rating : 4/5 (33 Downloads)

Book Synopsis Fundamentals of Statistical Signal Processing by : Steven M. Kay

Download or read book Fundamentals of Statistical Signal Processing written by Steven M. Kay and published by Pearson Education. This book was released on 2013 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.

Statistical Signal Processing in Engineering

Statistical Signal Processing in Engineering
Author :
Publisher : John Wiley & Sons
Total Pages : 604
Release :
ISBN-10 : 9781119293972
ISBN-13 : 1119293979
Rating : 4/5 (72 Downloads)

Book Synopsis Statistical Signal Processing in Engineering by : Umberto Spagnolini

Download or read book Statistical Signal Processing in Engineering written by Umberto Spagnolini and published by John Wiley & Sons. This book was released on 2018-02-05 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: A problem-solving approach to statistical signal processing for practicing engineers, technicians, and graduate students This book takes a pragmatic approach in solving a set of common problems engineers and technicians encounter when processing signals. In writing it, the author drew on his vast theoretical and practical experience in the field to provide a quick-solution manual for technicians and engineers, offering field-tested solutions to most problems engineers can encounter. At the same time, the book delineates the basic concepts and applied mathematics underlying each solution so that readers can go deeper into the theory to gain a better idea of the solution’s limitations and potential pitfalls, and thus tailor the best solution for the specific engineering application. Uniquely, Statistical Signal Processing in Engineering can also function as a textbook for engineering graduates and post-graduates. Dr. Spagnolini, who has had a quarter of a century of experience teaching graduate-level courses in digital and statistical signal processing methods, provides a detailed axiomatic presentation of the conceptual and mathematical foundations of statistical signal processing that will challenge students’ analytical skills and motivate them to develop new applications on their own, or better understand the motivation underlining the existing solutions. Throughout the book, some real-world examples demonstrate how powerful a tool statistical signal processing is in practice across a wide range of applications. Takes an interdisciplinary approach, integrating basic concepts and tools for statistical signal processing Informed by its author’s vast experience as both a practitioner and teacher Offers a hands-on approach to solving problems in statistical signal processing Covers a broad range of applications, including communication systems, machine learning, wavefield and array processing, remote sensing, image filtering and distributed computations Features numerous real-world examples from a wide range of applications showing the mathematical concepts involved in practice Includes MATLAB code of many of the experiments in the book Statistical Signal Processing in Engineering is an indispensable working resource for electrical engineers, especially those working in the information and communication technology (ICT) industry. It is also an ideal text for engineering students at large, applied mathematics post-graduates and advanced undergraduates in electrical engineering, applied statistics, and pure mathematics, studying statistical signal processing.