## About The Solution

## Overview

This second edition text focuses on the fundamentals of digital signal processing with an emphasis on practical applications. In order to motivate students, many of the examples illustrate the processing of speech and music. This theme is also a focus of the course software that features facilities for recording and playing sound on a standard PC. The accompanying website contains a comprehensive MATLAB software package called the Fundamentals of Digital Signal Processing (FDSP) toolbox version 2.0. The FDSP toolbox includes chapter GUI modules, an extensive library of DSP functions, direct access to all of the computational examples, figures, and tables, solutions to selected problems, and onliine help documentation. Using the interactive GUI modules, students can explore, compare, and directly experience the effects of signal processing techniques without any need for programming.

# Additional Product Information

## Features/Benefits

- Presents enough material, and sufficient flexibility in pedagogy, to provide for courses of different lengths.
- Experience with MATLAB programming is useful, but is not essential.
- A graphical user interface (GUI) module is included at the end of each chapter that allows students to investigate meaningful numerical applications without any need for programming.
- An FDSP toolbox and computational problems are supplied for those users who are familiar with MATLAB or are prepared to learn it, and are interested in developing their own implementations.
- Important terms are set apart for convenient reference using definitions, and key results are stated as theorems in order to highlight their significance. Detailed algorithms are also included to summarize the steps used to implement important design procedures.
- Each chapter starts with a concise summary of student learning objectives, with each objective cross-referenced to a section or sections within the chapter.
- Motivation sections in each chapter introduce one or more examples of practical problems that can be solved using techniques covered in the chapter.
- A series of analysis tools and signal processing techniques applicable to the type of problems covered are introduced in each chapter. Within these sections the analysis methods and processing techniques go from simple to more complex.
- Each chapter concludes with a generous set of homework problems organized by section and problem type.
- Instructor's Solution Manual with complete solutions to all problems includes the functions, examples, figures, and problems from the text, all directly accessible from an easy to use GUI driver program available exclusively for instructors.
- Homework Builder Module helps instructors create and distribute homework assignments and solutions using problems selected from the end-of-chapter exercise set.

## What's New

- New design – now divided into three major parts I. Signal and System Analysis, II. Digital Filter Design, III. Advanced Signal Processing.
- Expanded introduction to signals and systems.
- New examples and case studies as well as numerous new end-of-chapter problems.
- New sections on system identification and equalization, the inclusion of a novel quadrature filter design technique, as well as a discussion of sigma-delta ADC.
- Important definitions, propositions, algorithms, tables, and case studies are now summarized at the end of chapter.
- Version 2.0 of the FDSP toolbox companion software with expanded functionality.
- Expanded treatment of many topics such as: difference equations and block diagrams; Noncausal signals and systems; the discrete-time Fourier transform (DTFT); zero-phase FIR filters; polyphase filter realizations; quadrature mirror filter banks.

## Table of Contents

PART I. SIGNAL AND SYSTEM ANALYSIS.

1. SIGNAL PROCESSING.

Motivation. Signals and Systems. Sampling of Continuous-time Signals. Reconstruction of Continuous-time Signals. Prefilters and Postfilters. DAC and ADC Circuits. The FDSP Toolbox. GUI Software and Case Studies. Chapter Summary. Problems.

2. DISCRETE-TIME SYSTEMS IN THE TIME DOMAIN.

Motivation. Discrete-time Signals. Discrete-time Systems. Difference Equations. Block Diagrams. The Impulse Response. Convolution. Correlation. Stability in the Time Domain. GUI Software and Case Studies. Chapter Summary. Problems.

3. DISCRETE-TIME SYSTEMS IN THE FREQUENCY DOMAIN

Motivation. Z-transform Pairs. Z-transform Properties. Inverse Z-transform. Transfer Functions. Signal Flow Graphs. Stability in the Frequency Domain. Frequency Response. System Identification. GUI Software and Case Studies. Chapter Summary. Problems.

4. FOURIER TRANSFORMS AND SIGNAL ANALYSIS.

Motivation. Fourier Series. Discrete-time Fourier Transform (DTFT). Discrete Fourier Transform (DFT). Fast Fourier Transform (FFT). Fast Convolution and Correlation. White Noise. Auto-correlation. Zero Padding and Spectral Resolution. Spectrogram. Power Density Spectrum Estimation. GUI Software and Case Studies. Chapter Summary. Problems.

PART II. DIGITAL FILTER DESIGN.

5. FILTER DESIGN SPECIFICATIONS.

Motivation. Frequency-selective Filters. Linear-phase and Zero-phase Filters. Minimum-phase and Allpass Filters. Quadrature Filters. Notch Filters and Resonators. Narrowband Filters and Filter Banks.

Adaptive Filters. GUI Software and Case Study. Chapter Summary. Problems.

6. FIR FILTER DESIGN.

Motivation. Windowing Method. Frequency-sampling Method. Least-squares Method. Equiripple Filters. Differentiators and Hilbert Transformers. Quadrature Filters. Filter Realization Structures. Finite Word Length Effects. GUI Software and Case Study. Chapter Summary. Problems.

7. IIR FILTER DESIGN.

Motivation. Filter Design by Pole-zero Placement. Filter Design Parameters. Classical Analog Filters. Bilinear Transformation Method. Frequency Transformations. Filter Realization Structures. Finite Word Length Effects. GUI Software and Case Study. Chapter Summary. Problems.

PART III. ADVANCED SIGNAL PROCESSING.

8. MULTIRATE SIGNAL PROCESSING

Motivation. Integer Sampling Rate Converters. Rational Sampling Rate Converters. Multirate Filter Realization Structures. Narrowband Filters and Filter Banks. A Two-channel QMF Bank.

Oversampling ADC. Oversampling DAC. GUI Software and Case Study. Chapter Summary. Problems.

9. ADAPTIVE SIGNAL PROCESSING.

Motivation. Mean Square Error. The Least Mean Square (LMS) Method. Performance Analysis of the LMS Method. Modified LMS Methods. Adaptive FIR Filter Design. The Recursive Least Squares (RLS) Method. Active Noise Control. Nonlinear System Identification. GUI Software and Case Study. Chapter Summary. Problems.

REFERENCES AND FURTHER READING APPENDICES.

Transform Tables. Mathematical Identities. FDSP Toolbox Functions.

## Supplements

## Instructor Supplements

# Instructor Supplements

All supplements have been updated in coordination with the main title. Select the main title’s "About the Solution" tab, then select "What's New" for updates specific to title's edition.
**For more information about these supplements, or to obtain them, contact your Learning Consultant.**

###
Instructor Solutions Manual
(ISBN-10: 1111426031 | ISBN-13: 9781111426033)

Provides complete, worked-out solutions to all the problems in the text. Problems are divided into Analysis, GUI Simulation, and Computation categories and each problem is cross-referenced to a section within the chapter.

## Meet the Author

## About the Author

# Robert J. Schilling

Robert J. Schilling is Professor of Electrical and Computer Engineering at Clarkson University. Dr. Schilling's teaching interests include digital signal processing, control systems, robotics, nonlinear systems, computer graphics, and C++ and MATLAB programming. His research interests include adaptive signal processing, nonlinear system identification, active noise control, and control of robotic manipulators.

Robert J. Schilling is Professor of Electrical and Computer Engineering at Clarkson University. Dr. Schilling's teaching interests include digital signal processing, control systems, robotics, nonlinear systems, computer graphics, and C++ and MATLAB programming. His research interests include adaptive signal processing, nonlinear system identification, active noise control, and control of robotic manipulators.

# Sandra L. Harris

Sandra L. Harris is Associate Professor of Chemical Engineering at Clarkson University. Dr. Harris teaching interests include process control, thermodynamics, and biochemical engineering. Her research interests are centered on periodic processing, control of systems having varying dead times, and generation of input signals for efficient process identification.

Sandra L. Harris is Associate Professor of Chemical Engineering at Clarkson University. Dr. Harris teaching interests include process control, thermodynamics, and biochemical engineering. Her research interests are centered on periodic processing, control of systems having varying dead times, and generation of input signals for efficient process identification.

## Reviews

## Customer Reviews

"It has several features I like such as motivation section at beginning of each chapter, and applications and summary at the end of each chapter which helps not only to inspire the learning of the fundamental knowledge but also to accumulate the practical numerical experience in applying different DSP algorithms."

*— Guoxiang Gu, Louisiana State University *

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