Applied Digital Signal Processing Theory And Practice
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Applied Digital Signal Processing Theory And Practice

Applied Digital Signal Processing Theory And Practice by Dimitris G. Manolakis and Vinay K. Ingle | PDF Free Download.

Authors of Applied Digital Signal Processing Theory And Practice

Dimitris G. Manolakis is currently a Member of Technical Staff at MIT Lincoln Laboratory in Lexington, Massachusetts.

Prior to this, he was a Principal Member of Research Staff at Riverside Research Institute. Since receiving his Ph.D. in Electrical Engineering from the University of Athens in 1981, he has taught at various institutions including Northeastern University, Boston College, and Worcester Polytechnic Institute, and co-authored two textbooks on signal processing.

His research experience and interests include the areas of digital signal processing, adaptive filtering, array processing, pattern recognition, remote sensing, and radar systems.

Vinay K. Ingle is currently an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University, where he has worked since 1981 after receiving his Ph.D. in Electrical and Computer Engineering from Rensselaer Polytechnic Institute.

He has taught both undergraduate and graduate courses in many diverse areas including systems, signal/image processing, communications, and control theory, and has co-authored several textbooks on signal processing.

He has broad research experience in the areas of signal and image processing, stochastic processes, and estimation theory. Currently, he is actively involved in hyperspectral imaging and signal processing.

Applied Digital Signal Processing Contents

  • Introduction
  • Discrete-time signals and systems
  • The z-transform
  • Fourier representation of signals
  • Transform analysis of LTI systems
  • A sampling of continuous-time signals
  • The Discrete Fourier Transform
  • Computation of the Discrete Fourier Transform
  • Structures for discrete-time systems
  • Design of FIR filters
  • Design of IIR filters
  • Multirate signal processing
  • Random signals
  • Random signal processing
  • Finite wordlength effects

Preface to Applied Digital Signal Processing Theory And Practice

During the last three decades, Digital Signal Processing (DSP) has evolved into a core area of study in electrical and computer engineering.

Today, DSP provides the methodology and algorithms for the solution of a continuously growing number of practical problems in scientific, engineering, and multimedia applications.

Despite the existence of a number of excellent textbooks focusing either on the theory of DSP or on the application of DSP algorithms using interactive software packages, we feel there is a strong need for a book bridging the two approaches by combining the best of both worlds.

This was our motivation for writing this book, that is, to help students and practicing engineers understand the fundamental mathematical principles underlying the operation of a DSP method, appreciate its practical limitations, and grasp, with sufficient details, its practical implementation.


The principal objective of this book is to provide a systematic introduction to the basic concepts and methodologies for digital signal processing, based whenever possible on fundamental principles.

A secondary objective is to develop a foundation that can be used by students, researchers, and practicing engineers as the basis for further study and research in this field.

To achieve these objectives, we have focused on material that is fundamental and where the scope of application is not limited to the solution of specialized problems, that is, material that has a broad scope of application.

Our aim is to help the student develop sufficient intuition as to how a DSP technique works, be able to apply the technique and be capable of interpreting the results of the application.

We believe this approach will also help students to become intelligent users of DSP techniques and good critics of DSP techniques performed by others.

Pedagogical philosophy

Our experience in teaching undergraduate and graduate courses in digital signal processing has reaffirmed the belief that the ideal blend of simplified mathematical analysis and computer-based reasoning and simulations enhances both the teaching and the learning of digital signal processing.

To achieve these objectives, we have used mathematics to support underlying intuition rather than as a substitute for it, and we have emphasized practicality without turning the book into a simplistic “cookbook.”

The purpose of MATLAB code integrated with the text is to illustrate the implementation of core signal processing algorithms; therefore, we use standard language commands and functions that have remained relatively stable during the most recent releases.

We also believe that an in-depth understanding and full appreciation of DSP is not possible without familiarity with the fundamentals of continuous-time signals and systems.

To help the reader grasp the full potential of DSP theory and its application to practical problems, which primarily involve continuous-time signals, we have integrated relevant continuous-time background into the text.

This material can be quickly reviewed or skipped by readers already exposed to the theory of continuous-time signals and systems. Another advantage of this approach is that some concepts are easier to explain and analyze in continuous-time than in discrete-time or vice versa.

Audience and prerequisites

The book is primarily aimed as a textbook for upper-level undergraduate and for first-year graduate students in electrical and computer engineering. However, researchers, engineers, and industry practitioners can use the book to learn how to analyze or process data for scientific or engineering applications.

The mathematical complexity has been kept at a level suitable for seniors and first-year graduate students in almost any technical discipline. More specifically, the reader should have a background in calculus, complex numbers and variables, and the basics of linear algebra (vectors, matrices, and their manipulation).

Course configurations

The material covered in this text is intended for teaching to upper-level undergraduate or first-year graduate students. However, it can be used flexibly for the preparation of a number of courses.

The first six chapters can be used in junior-level signals and systems course with emphasis on discrete-time. The first 11 chapters can be used in a typical one-semester undergraduate or graduate DSP course in which the first six chapters are reviewed and the remaining five chapters are emphasized.

Finally, an advanced graduate-level course on modern signal processing can be taught by combining some appropriate material from the first 11 chapters and emphasizing the last four chapters.

The pedagogical coverage of the material also lends itself to a well-rounded graduate-level course in DSP by choosing selected topics from all chapters.


Experience has taught us that errors – typos or just plain mistakes – are an inescapable byproduct of any textbook writing endeavor.

We apologize in advance for any errors you may find and we urge you to bring them or additional feedback to our attention at [email protected]

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