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Digital Signal Processing: Principles, Algorithms, and Applications
A significant revision of a best-selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science.The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing.
1104 pages, Hardcover
First published January 16, 1992
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Displaying 1 - 23 of 23 reviews
January 17, 2022
Perfect book. But not for reading. Every single thing is described in maximum detail by the authors; therefore, it is boring to read but great to find solutions.
I consider this book being equivalent to stackoverflow.com for engineers.
I consider this book being equivalent to stackoverflow.com for engineers.
February 22, 2022
Digital Signal Processing: Principles, Algorithms, and Applications by John G. Proakis and Dimitris G. Manolakis is one of the most substantial textbooks in the field of digital signal processing (DSP). Written primarily for students and practitioners in electrical and computer engineering, the book combines mathematical theory, signal-processing algorithms, and practical implementation in a way that has made it a long-standing reference for university courses and professional study. The defining characteristic of the book is its rigorous treatment of DSP fundamentals. Rather than introducing concepts primarily through intuition or simplified examples, Proakis and Manolakis develop the mathematical framework underlying digital signal processing and then show how that framework leads to practical algorithms. This approach makes the book demanding, but it also gives it considerable depth and longevity.
Scope and Content
The book covers the central concepts that form the foundation of DSP. These include discrete-time signals and systems, linear time-invariant systems, convolution, difference equations, the z-transform, frequency-domain analysis, the discrete Fourier transform (DFT), and the Fast Fourier Transform (FFT). It also provides extensive coverage of digital filter design, including both finite impulse response (FIR) and infinite impulse response (IIR) filters. One of the book's major strengths is the connection it establishes between theory and implementation. Mathematical expressions are not presented simply as abstract exercises; they are used to develop algorithms that can be implemented computationally. This is particularly valuable for engineering students, for whom understanding both why an algorithm works and how to implement it is essential. The treatment of spectral analysis and Fourier techniques is especially important. The FFT, for example, is not merely introduced as a computational shortcut for calculating the DFT. The text places such algorithms within the broader mathematical structure of discrete-time signal analysis. This provides readers with a stronger understanding of when and why particular methods are useful. Later editions have expanded the scope of the subject further, incorporating topics such as multirate signal processing, filter banks, wavelets, short-time Fourier analysis, and newer computational approaches. Consequently, the book can function not only as an introduction to the core principles of DSP but also as a reference for more advanced study.
Mathematical Rigor
The book's greatest strength is also one of its principal challenges: its mathematical density. Proakis and Manolakis do not shy away from derivations. Important results are frequently developed rather than simply stated, giving the reader an opportunity to understand the reasoning behind the formulas and algorithms. For students who already possess a solid background in calculus, linear systems, Fourier analysis, and related engineering mathematics, this rigor can be extremely rewarding. However, readers approaching DSP for the first time may find the presentation difficult. The book is not designed as a gentle, intuition-first introduction. A reader without a strong mathematical foundation may find themselves concentrating more on manipulating equations than on understanding the physical meaning of the signals being studied. This distinction is important because DSP sits at the intersection of mathematics, engineering, and programming. A newcomer may want to know what a filter does before learning the mathematical machinery that describes it. Proakis and Manolakis often take the opposite route: establish the theory first and then apply it. That makes the text particularly suitable for formal engineering education, but potentially less accessible for casual learners or programmers entering DSP from a software background.
Practical Orientation
Despite its theoretical emphasis, the book is far from purely academic. Its substantial collection of exercises and computer-based problems gives readers opportunities to apply concepts computationally. Problems involving tools such as MATLAB and programming languages help bridge the gap between equations on a page and algorithms running on a computer. This practical component is particularly useful because DSP is ultimately an applied discipline. Understanding the DFT, for example, is one thing; implementing it, interpreting its output, understanding spectral leakage, and choosing an appropriate computational method are different skills. The book's exercises encourage readers to develop both types of understanding.
For students studying electrical or computer engineering, this combination can make the book especially valuable as a course companion. Working through the problems is likely to be much more beneficial than simply reading the chapters, since many of the book's concepts become clearer when translated into calculations, simulations, and programs.
Scope and Content
The book covers the central concepts that form the foundation of DSP. These include discrete-time signals and systems, linear time-invariant systems, convolution, difference equations, the z-transform, frequency-domain analysis, the discrete Fourier transform (DFT), and the Fast Fourier Transform (FFT). It also provides extensive coverage of digital filter design, including both finite impulse response (FIR) and infinite impulse response (IIR) filters. One of the book's major strengths is the connection it establishes between theory and implementation. Mathematical expressions are not presented simply as abstract exercises; they are used to develop algorithms that can be implemented computationally. This is particularly valuable for engineering students, for whom understanding both why an algorithm works and how to implement it is essential. The treatment of spectral analysis and Fourier techniques is especially important. The FFT, for example, is not merely introduced as a computational shortcut for calculating the DFT. The text places such algorithms within the broader mathematical structure of discrete-time signal analysis. This provides readers with a stronger understanding of when and why particular methods are useful. Later editions have expanded the scope of the subject further, incorporating topics such as multirate signal processing, filter banks, wavelets, short-time Fourier analysis, and newer computational approaches. Consequently, the book can function not only as an introduction to the core principles of DSP but also as a reference for more advanced study.
Mathematical Rigor
The book's greatest strength is also one of its principal challenges: its mathematical density. Proakis and Manolakis do not shy away from derivations. Important results are frequently developed rather than simply stated, giving the reader an opportunity to understand the reasoning behind the formulas and algorithms. For students who already possess a solid background in calculus, linear systems, Fourier analysis, and related engineering mathematics, this rigor can be extremely rewarding. However, readers approaching DSP for the first time may find the presentation difficult. The book is not designed as a gentle, intuition-first introduction. A reader without a strong mathematical foundation may find themselves concentrating more on manipulating equations than on understanding the physical meaning of the signals being studied. This distinction is important because DSP sits at the intersection of mathematics, engineering, and programming. A newcomer may want to know what a filter does before learning the mathematical machinery that describes it. Proakis and Manolakis often take the opposite route: establish the theory first and then apply it. That makes the text particularly suitable for formal engineering education, but potentially less accessible for casual learners or programmers entering DSP from a software background.
Practical Orientation
Despite its theoretical emphasis, the book is far from purely academic. Its substantial collection of exercises and computer-based problems gives readers opportunities to apply concepts computationally. Problems involving tools such as MATLAB and programming languages help bridge the gap between equations on a page and algorithms running on a computer. This practical component is particularly useful because DSP is ultimately an applied discipline. Understanding the DFT, for example, is one thing; implementing it, interpreting its output, understanding spectral leakage, and choosing an appropriate computational method are different skills. The book's exercises encourage readers to develop both types of understanding.
For students studying electrical or computer engineering, this combination can make the book especially valuable as a course companion. Working through the problems is likely to be much more beneficial than simply reading the chapters, since many of the book's concepts become clearer when translated into calculations, simulations, and programs.
February 18, 2010
The essential textbook on DSP. 4th year EE coursebook
March 2, 2013
I just wish I had more time to read this book! This is THE best book for Signal Processing. Lucid and Comprehensive.
May 14, 2013
its a gud book to be reffered for the exams.
Want to Read
November 24, 2014It's a wonderful book for me to read about Digital Signal Processing.
February 15, 2025
Pros: This is the textbook for a DSP course at my university.
Cons: I find that the book contains numerous errors in mathematical notation, making it both confusing and time-consuming to interpret and understand.
For example, in the discrete-time system, the author denotes y(n) = T(x(n)), which is incorrect in function notation. From my perspective, the correct notation should be y(n) = [T(x)](n). Here, T(x) represents a mapping that operates on a sequence (either finite or infinite) and produces another sequence, y, with n serving as the index of the new sequence.
In addition, in the chapter Discrete-time signal and system, the author wrote the Convolution formula as y(n) = h(n) * x(n). This is a completely incorrect mathematical formulation. Even though the Convolution formulas on Wikipedia are defined more precisely (https://en.wikipedia.org/wiki/Convolu...).
There are numerous other mathematical errors.
If the author adhered more strictly to mathematical notation, I would be able to read and understand this book and its principles more quickly
Cons: I find that the book contains numerous errors in mathematical notation, making it both confusing and time-consuming to interpret and understand.
For example, in the discrete-time system, the author denotes y(n) = T(x(n)), which is incorrect in function notation. From my perspective, the correct notation should be y(n) = [T(x)](n). Here, T(x) represents a mapping that operates on a sequence (either finite or infinite) and produces another sequence, y, with n serving as the index of the new sequence.
In addition, in the chapter Discrete-time signal and system, the author wrote the Convolution formula as y(n) = h(n) * x(n). This is a completely incorrect mathematical formulation. Even though the Convolution formulas on Wikipedia are defined more precisely (https://en.wikipedia.org/wiki/Convolu...).
There are numerous other mathematical errors.
If the author adhered more strictly to mathematical notation, I would be able to read and understand this book and its principles more quickly
December 5, 2025
sucks. Just really sucks. Many a painful hour has been spent on this flaming pile of garbage. Maybe the book was just written for people vastly more intelligent than I, but I found it very challenging to understand. You MUST be very very very good at math to understand this completely. Would not recommend for those who are looking for a gentle introduction. The ratio of words to math is like 1/2. Literally incomprehensible unless you're some kind of wizard. Oh, yeah, and also there's like a bunch of mistakes in the book and solutions manual. So have fun wasting an entire day trying to figure out why you messed up a problem, when it was actually just a mistake in the book :))
October 8, 2017
Though not clear and intuitive in the first go, you see the beauty as you read and re-read. This is not an introductory text in Digital Signal Processing, some intuitions, or rather the required maturity, has to be formed before considering reading this book.
Read
July 6, 2019Lpi
Read
June 22, 2022l;kjn
July 14, 2023
I hate you even more
May 17, 2025
It's helpful in electrical engineering works
This entire review has been hidden because of spoilers.
December 8, 2016
For a complete newbie to Digital Signal Processing, this was a clear and fun read. Notation was very clear, lots of examples, and good amount of topics covered. I used this alongside a Masters level SSP course with no prior signal theory experience and didn't get too lost - so the book did it's job as a student text!
May 30, 2009
Although it takes some getting used to, once you get comfortable with it, this is a great DSP text. Good explanations about the underlying math, and also some helpful practical examples of application. My first point of reference for DSP math.
September 2, 2007
Buku ini adalah buku teks mata kuliah, Pengolahan Sinyal Digital. Dan, mau tahu aku dapat nilai apa? A! Yippie....
October 29, 2008
Textbook for ECE 437, Digital Signal Processing I.
February 19, 2011
لا تقررررب !!
Want to Read
August 24, 2011i am happy ,i get this book.
Read
October 10, 2013i thnks its a good book for digital process
May 11, 2014
Undoubtedly this is the best book for digital signal processing.
Displaying 1 - 23 of 23 reviews