A digital filter can be pictured as a "black box" that accepts a sequence of numbers and emits a new sequence of numbers. In digital audio signal processing applications, such number sequences usually represent sounds. For example, digital filters are used to implement graphic equalizers and other digital audio effects. This book is a gentle introduction to digital filters, including mathematical theory, illustrative examples, some audio applications, and useful software starting points. The theory treatment begins at the high-school level, and covers fundamental concepts in linear systems theory and digital filter analysis. Various "small" digital filters are analyzed as examples, particularly those commonly used in audio applications. Matlab programming examples are emphasized for illustrating the use and development of digital filters in practice.

This textbook provides comprehensive coverage for courses in the basics of design and implementation of digital filters. The book assumes only basic knowledge in digital signal processing and covers state-of-the-art methods for digital filter design and provides a simple route for the readers to design their own filters. The advanced mathematics that is required for the filter design is minimized by providing an extensive MATLAB toolbox with over 300 files. The book presents over 200 design examples with MATLAB code and over 300 problems to be solved by the reader. The students can design and modify the code for their use. The book and the design examples cover almost all known design methods of frequency-selective digital filters as well as some of the authors’ own, unique techniques.

Introduction to digital filters. Finite impulse-response filters. Design of linear-phase finite impulse-response. Minimum-phas and complex approximation. Implementation of finite impulse-response filters. Properties of infinite impulse-response filters. Design of infinite impulse-response filters. Implementation of infinite impulse-response filters. Programs.

The book is not an exposition on digital signal processing (DSP) but rather a treatise on digital filters. The material and coverage is comprehensive, presented in a consistent that first develops topics and subtopics in terms it their purpose, relationship to other core ideas, theoretical and conceptual framework, and finally instruction in the implementation of digital filter devices. Each major study is supported by Matlab-enabled activities and examples, with each Chapter culminating in a comprehensive design case study.

This textbook provides an insight into the characteristics and design of digital filters. It includes tables of filter parameters for Butterworth, Chbeyshev, Cauer and Bessel filters and several computer routines for filter design programs.

The function of a filter is to transform a signal into another one more suit able for a given purpose. As such, filters find applications in telecommunica tions, radar, sonar, remote sensing, geophysical signal processing, image pro cessing, and computer vision. Numerous authors have considered deterministic and statistical approaches for the study of passive, active, digital, multidimen sional, and adaptive filters. Most of the filters considered were linear although the theory of nonlinear filters is developing rapidly, as it is evident by the numerous research papers and a few specialized monographs now available. Our research interests in this area created opportunity for cooperation and co authored publications during the past few years in many nonlinear filter families described in this book. As a result of this cooperation and a visit from John Pitas on a research leave at the University of Toronto in September 1988, the idea for this book was first conceived. The difficulty in writing such a mono graph was that the area seemed fragmented and no general theory was available to encompass the many different kinds of filters presented in the literature. However, the similarities of some families of nonlinear filters and the need for such a monograph providing a broad overview of the whole area made the pro ject worthwhile. The result is the book now in your hands, typeset at the Department of Electrical Engineering of the University of Toronto during the summer of 1989.

This text provides a broad introduction to the field of digital signal processing and contains sufficient material for a two-semester sequence in this multifaceted subject. It is also written with the practicing engineer or scientist in mind, having many observations and examples of practical significance drawn from the author's industrial experience. The first semester, at the junior, senior, or first-year graduate level, could cover chapters 2 through 7 with topics perhaps from chapters 8 and 9, depending upon the background of the students. The only requisite background is linear systems theory for continuous-time systems, including Fourier and Laplace trans forms. Many students will also have had some previous exposure to discrete-time systems, in which case chapters 2 through 4 may serve to review and expand that preparation. Note, in particular, that knowledge of probability theory and random processes is not required until chapters 10 and 11, except for section 7. 6 on the periodogram. A second, advanced course could utilize material from chapters 8 through 13. A comprehensive one-semester course for suitably prepared graduate students might cover chapters 4 through 9 and additional topics from chapters 10 through 13. Sections marked with a dagger Ct) cover advanced or specialized topics and may be skipped without loss of continuity. Notable features of the book include the following: 1. Numerous useful filter examples early in the text in chapters 4 and 5. 2. State-space representation and structures in chapters 4 and 11.