Suitable for a one- or two-semester undergraduate-level electrical engineering, computer engineering, and computer science course in Discrete Systems and Digital Signal Processing. Assumes some prior knowledge of advanced calculus, linear systems for continuous-time signals, and Fourier series and transforms. Giving students a sound balance of theory and practical application, this no-nonsense text presents the fundamental concepts and techniques of modern digital signal processing with related algorithms and applications. Covering both time-domain and frequency- domain methods for the analysis of linear, discrete-time systems, the book offers cutting-edge coverage on such topics as sampling, digital filter design, filter realizations, deconvolution, interpolation, decimation, state-space methods, spectrum analysis, and more. Rigorous and challenging, it further prepares students with numerous examples, exercises, and experiments emphasizing software implementation of digital signal processing algorithms integrated throughout.

Digital Signal Processing: Principles, Algorithms, and Applications

Computers & Technology

Proakis, John G.

Manolakis, Dimitris G.

Networking & Cloud Computing

Macmillan Coll Div

Introduction to Digital Signal Processing

Engineering & Transportation

Engineering

Prentice Hall (Higher Education Division, Pearson Education)

This book is intended for graduate students at the first year or advanced graduate level in the areas of statistical and adaptive signal processing, as well as practicing engineers. The goal of this book is to provide a unified, complete, and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing. The text is written in an intuitive manner and includes many illustrative examples. In addition a sufficient number of computer based experiments are included that illustrate important concepts to the reader for ease of implementation. Throughout the book a sufficient emphasis has been placed on applications for the purposes of demonstrating the utility of various techniques.

Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing

Ingle, Vinay K.

Kogon, Stephen M.

Mcgraw-Hill College

Presents the fundamentals of discrete-time signals, systems, and modern digital processing algorithms and applications for students in electrical engineering, computer engineering, and computer science. Textbook. DLC: Signal processing - Digital techniques.

Digital Signal Processing: Principles, Algorithms and Applications (3rd Edition)

PRENTICE/HALL

Master the basic concepts and methodologies of digital signal processing with this systematic introduction, without the need for an extensive mathematical background. The authors lead the reader through the fundamental mathematical principles underlying the operation of key signal processing techniques, providing simple arguments and cases rather than detailed general proofs. Coverage of practical implementation, discussion of the limitations of particular methods and plentiful MATLAB illustrations allow readers to better connect theory and practice. A focus on algorithms that are of theoretical importance or useful in real-world applications ensures that students cover material relevant to engineering practice, and equips students and practitioners alike with the basic principles necessary to apply DSP techniques to a variety of applications. Chapters include worked examples, problems and computer experiments, helping students to absorb the material they have just read. Lecture slides for all figures and solutions to the numerous problems are available to instructors.

Applied Digital Signal Processing: Theory and Practice

Cambridge University Press

Master the basic concepts and methodologies of digital signal processing with this systematic introduction, without the need for an extensive mathematical background. The authors lead the reader through the fundamental mathematical principles underlying the operation of key signal processing techniques, providing simple arguments and cases rather than detailed general proofs. Coverage of practical implementation, discussion of the limitations of particular methods and plentiful MATLAB illustrations allow readers to better connect theory and practice. A focus on algorithms that are of theoretical importance or useful in real-world applications ensures that students cover material relevant to engineering practice, and equips students and practitioners alike with the basic principles necessary to apply DSP techniques to a variety of applications. Chapters include worked examples, problems and computer experiments, helping students to absorb the material they have just read. Lecture slides for all figures and solutions to the numerous problems are available to instructors.

A practical and self-contained guide to the principles, techniques, models and tools of imaging spectroscopy. Bringing together material from essential physics and digital signal processing, it covers key topics such as sensor design and calibration, atmospheric inversion and model techniques, and processing and exploitation algorithms. Readers will learn how to apply the main algorithms to practical problems, how to choose the best algorithm for a particular application, and how to process and interpret hyperspectral imaging data. A wealth of additional materials accompany the book online, including example projects and data for students, and problem solutions and viewgraphs for instructors. This is an essential text for senior undergraduate and graduate students looking to learn the fundamentals of imaging spectroscopy, and an invaluable reference for scientists and engineers working in the field.

Hyperspectral Imaging Remote Sensing: Physics, Sensors, and Algorithms

Arts & Photography

Lockwood, Ronald B.

Cooley, Thomas W.

Photography & Video

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. From the fundamentals of discrete-time signal processing and linear signal models, to optimum linear filters and least-squares filtering and prediction, you get in-depth information on a broad range of critical topics from leading experts in industry and academia. This invaluable reference provides clear examples, problem sets, and computer experiments that help you master the material and learn how to implement various methods presented in the book. You also find a set of Matlab® functions that illustrate the use of various techniques and can be used to solve real-world problems in the field.

Artech House

See the best price to sell, buy, or rent books by Manolakis, Dimitris G.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Manolakis, Dimitris G.

See the best price to sell, buy, or rent books by Manolakis, Dimitris G.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Digital Signal Processing: Principles, Algorithms, and Applications

Introduction to Digital Signal Processing

Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing

Digital Signal Processing: Principles, Algorithms and Applications (3rd Edition)

Applied Digital Signal Processing: Theory and Practice

Applied Digital Signal Processing: Theory and Practice

Hyperspectral Imaging Remote Sensing: Physics, Sensors, and Algorithms

Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing