Samir I. Abood - Digital Signal Processing: A Primer with MATLAB®

Digital Signal Processing

A Primer With MATLAB

Dedicated to

My great parents, who never stop giving of themselves in countless ways,

My beloved brothers and sisters;

My dearest wife, who offered me unconditional love with the light of hope and support;

My beloved kids: Daniah, and Mustafa, whom I can't force myself to stop loving;

To all my family, the symbol of love and giving.

Digital Signal Processing

A Primer With MATLAB

Samir I. Abood

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Contents

I appreciate the suggestions and comments from several reviewers, including assistance from Prof. Zainab Ibrahim/University of Baghdad/Electrical Engineering Department, Dr. Muna Fayyadh/Colorado Technical University, and special thanks to Nafisa Islam/Prairie View A&M University Their frank and positive criticisms led to considerable improvement of this work.

Finally, I express my profound gratitude to my wife and children, without whose cooperation this project would have been challenging if not impossible. We appreciate feedback from students, professors, and other users of this book. I can be reached at sameeralrifaee74@ieee.org sabood@student.pvamu.edu and sameeralrifaee74@gmail.com.

Digital signal processing (DSP) denotes various techniques for improving the accuracy and reliability of digital communications. The philosophy behind DSP is quite complicated. Digital signal processing converts signals from an analog form into digital data that can then be analyzed and consequently turned back into an analog signal with improved quality after the DSP system has finished its work.

In DSP, the engineers usually study digital signals in one of the following domains: time domains, frequency domains, spatial domains, and wavelet domains.

The applications of DSP include digital image processing, audio signal processing, audio compression, speech processing, video compression, digital communications, digital synthesizers, speech recognition radar systems, ultrasound and sonar, financial signal processing, seismology, and biomedicine.

The DSP algorithms can be run on general-purpose computers and implemented using software code program, and Simulink also can implement by using hardware as modern technologies for digital signal processing include more powerful general-purpose controllers, microprocessors, stream processors, and field-programmable gate arrays (FPGAs).

The typical processing approach in the time domain is an improvement of the input signal through a method called filtering. In digital filters there are two types of filter with and without feedback. There are various ways to characterize filters: as a linear filter, causal filter, time-invariant filter, stable filter, finite impulse response (FIR) filter, and infinite impulse response (IIR) filter.

The signals are converted from the time domain to the frequency domain usually through the use of the Fourier Transform. The Fourier Transform, also called spectrum or spectral analysis, converts the time information into a magnitude and phase component of each frequency. The engineer needs to study the spectrum to control which frequencies are present in the input signal and which are missing.

Digital filters originate in both IIR and FIR types. While FIR filters are always stable, IIR filters have feedback loops that may become unstable and oscillate. Digital filters can be analyzed through the z-transform, which provides a tool for analyzing stability issues of digital IIR filters. Also, it is analogous to the analyse and designs analog IIR filters represent the Laplace transform

The book offers a good understanding of a signals behavior and its applications. The book begins with the study of signals and systems. Then it presents their applications in the different types of configurations shown in lucid detail. The book presents the relation of signals and systems. This book is intended for college students, both in community colleges and universities.

This book is organized into 16 chapters. With a short review of the basic concept of continuous and discrete signals in .

. The chapter also elaborates on the method of decimation-in-frequency and in time.

In introduces pole-zero stability, difference equations and transfer function, and the stability of DSP systems.

presents the implementation of IIR digital filters and their properties and the design of a notch filter by MATLAB.

deals with the implementation of Finite Impulse Response (FIR), and it is design.

deals with the digital filter design, the realization of digital filters, and direction-form I realization.

Earlier experience using the MATLAB program is not needed since the author highly recommends that the reader studies this material in conjunction with the MATLAB Student Version. and Appendix C of this text provides a practical introduction to MATLAB.

MATLAB is a registered trademark of The MathWorks, Inc. For product information, please contact:

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