The book discusses receiving signals that most electrical engineers detect and study. The vast majority of signals could never be detected due to random additive signals, known as noise, that distorts them or completely overshadows them. Such examples include an audio signal of the pilot communicating with the ground over the engine noise or a bioengineer listening for a fetus’ heartbeat over the mother’s. The text presents the methods for extracting the desired signals from the noise. Each new development includes examples and exercises that use MATLAB to provide the answer in graphic forms for the reader's comprehension and understanding.

This book is Volume I of the series DSP for MATLAB(TM) and LabVIEW(TM). The entire series consists of four volumes that collectively cover basic digital signal processing in a practical and accessible manner, but which nonetheless include all essential foundation mathematics. As the series title implies, the scripts (of which there are more than 200) described in the text and supplied in code form (available at www.morganclaypool.com/page/isen) will run on both MATLAB and LabVIEW. Volume I consists of four chapters. The first chapter gives a brief overview of the field of digital signal processing. This is followed by a chapter detailing many useful signals and concepts, including convolution, recursion, difference equations, LTI systems, etc. The third chapter covers conversion from the continuous to discrete domain and back (i.e., analog-to-digital and digital-to-analog conversion), aliasing, the Nyquist rate, normalized frequency, conversion from one sample rate to another, waveform generation at various sample rates from stored wave data, and Mu-law compression. The fourth and final chapter of the present volume introduces the reader to many important principles of signal processing, including correlation, the correlation sequence, the Real DFT, correlation by convolution, matched filtering, simple FIR filters, and simple IIR filters. Chapter 4, in particular, provides an intuitive or "first principle" understanding of how digital filtering and frequency transforms work, preparing the reader for Volumes II and III, which provide, respectively, detailed coverage of discrete frequency transforms (including the Discrete Time Fourier Transform, the Discrete Fourier Transform, and the z-Transform) and digital filter design (FIR design using Windowing, Frequency Sampling, and Optimum Equiripple techniques, and Classical IIR design). Volume IV, the culmination of the series, is an introductory treatment of LMS Adaptive Filtering and applications. The text for all volumes contains many examples, and many useful computational scripts, augmented by demonstration scripts and LabVIEW Virtual Instruments (VIs) that can be run to illustrate various signal processing concepts graphically on the user's computer screen. Table of Contents: An Overview of DSP / Discrete Signals and Concepts / Sampling and Binary Representation / Transform and Filtering Principles

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A practical and accessible guide to understanding digital signal processingIntroduction to Digital Signal Processing and Filter Design was developed and fine-tuned from the author's twenty-five years of experience teaching classes in digital signal processing.

What are the relations between continuous-time and discrete-time/sampled-data systems, signals, and their spectra? How can digital systems be designed to replace existing analog systems? What is the reason for having so many transforms, and how do you know which one to use? What do s and z really means and how are they related? How can you use the fast Fourier transform (FFT) and other digital signal processing (DSP) algorithms to successfully process sampled signals? Inside, you'll find the answers to these and other fundamental questions on DSP. You'll gain a solid understanding of the key principles that will help you compare, select, and properly use existing DSP algorithms for an application. You'll also learn how to create original working algorithms or conceptual insights, design frequency-selective and optimal digital filters, participate in DSP research, and select or construct appropriate hardware implementations. Key Features * MATLAB graphics are integrated throughout the text to help clarify DSP concepts. Complete numerical examples clearly illustrate the practical uses of DSP. * Uniquely detailed coverage of fundamental DSP principles provides the rationales behind definitions, algorithms, and transform properties. * Practical real-world examples combined with a student-friendly writing style enhance the material. * Unexpected results and thought-provoking questions are provided to further spark reader interest. * Over 525 end-of-chapter problems are included, with complete solutions available to the instructor (168 are MATLAB-oriented).

Intended to supplement traditional references on digital signal processing (DSP) for readers who wish to make MATLAB an integral part of DSP, this text covers such topics as Discrete-time signals and systems, Discrete-time Fourier analysis, the z-Transform, the Discrete Fourier Transform, digital filter structures, FIR filter design, IIR filter design, and more.

Converting analog to digital signals and vice versa -- Time-domain representation of discrete-time signals and systems -- Frequency-domain representation of discrete-time signals -- DSP application examples -- Finite impulse response filter design -- Infinite impulse response (IIR) filter design -- Digital filter realizations -- Digital signal processors -- Hardware and software development tools.