Introduction to Digital Signal Processing

This book approaches digital signal processing and filter design in a novel way, by presenting the relevant theory and then having the student apply it by implementing signal processing routines on a computer. This mixture of theory and application has worked successfully. With this approach, the students receive a deeper and intuitive understanding of the theory, its applications and its limitations. This text also includes projects that require students to write computer programs to accomplish signal processing projects. Features • The text has the flexibility of being used in a wide variety of digital signal processing courses at the undergraduate and graduate levels. • In addition to the Problems, a set of Computer Projects is included, the programs for which should be written by the student. • Instructions for program development are included as an integral part of the text and Project description. • Two advanced topics are covered in describing the effects of finite precision encountered in practical hardware implementation of digital filters and an overview of inverse filters. Contents 1. Introduction 2. Discrete-time Description of Signals and Systems 3. Fourier Transform of Discrete time Signals 4. The Discrete Fourier Transform 5. The z-transform 6. Digital Filter Structures 7. From Analysis to Synthesis 8. Infinite Impulse Response Filter Design Techniques 9. Finite Impulse Response Filter Design Techniques 10. Finite-precision Effects 11. Inverse Filtering. About the Author Roman Kuc received the B.S.E.E. degree from the Illinois Institute of Technology, Chicago, in 1968, and the Ph.D. degree in Eletrical Engineering from Columbia University, New York, in 1977. From 1968 to 1975 he was a Member of the Technical Staff of Bell Telephone Laboratories, where he was engaged in the design of audo-recording instrumentation and in developing efficient digital-speech coding techniques. From 1977 to 1979 he was a postdoctoral Research Associate in the Department of Electrical Engineering, Columbia Univeristy, and the Radiology Department of St. Luke’s Hosital, New York, where he employed statistical estimation techiques to extract diagnostic information from reflected ultrasound signals. As an Associate Professor with the Department of Electrical Engineering, Yale University, New Heaven, CT, he is currently pursuing problems in ultrasonic tissue characterization, speech recognition, and intelligent acoustic sensors for robotic applications. Dr. Kuc is an Associate Editor of the IEEE Transactions on Acoustics, Speech, and Signal processing and Ultrasonic imaging. He is also the Consulting Editor of Electrical Engineering for The American Scientist and a past Chairman of the Instrumentation Section of the New York Academy of Sciences.