Representations of Musical Signals describes a new generation of digital audio and computer music systems made possible by recent advances in digital signal processing theory, hardware design, and programming techniques. It explores new representations of musical signals that can have profound effects on the way musicians conceive of and realize musical ideas. In particular, the book focuses on models that combine time-domain and frequency-domain representations (grains, wavelets, and physical models), visual programming and advanced user interfaces, and that incorporate musical knowledge using artificial intelligence techniques and adaptive neural networks. The 14 contributions take up issues of how musical signals should be displayed to musicians, engineers, and scientists who want to work with them, how professionals can work with the representations to accomplish musical tasks, how systems can be designed to permit working with multiple views of the same signal, and how representations of musical signals should be organized to promote efficient communication between devices using these signals. Giovanni DePoli is a member of the faculty of the Department of Informatics and Electronics at the University of Padua. Aldo Piccialli is a member of the faculty of the Department of Physics at the University of Naples. Curtis Roads is a composer and consulting editor of Computer Music Journal. Contributors: J. M. Adrien. D. Arfib. R. D'Autilia. C. Cadoz. S. Cavaliere G. De Poli, G. Evangelista. J. Florens. G. Garnett. A. Grossman. F. Guerra. K. Hebei. R. Kronland­Martinet. C. Lischka. A. Piccialli. J-C. Risset. C. Roads. C. Scaletti., J. Sundberg.

Compiled by an international array of musical and technical specialists, this book deals with some of the most important topics in modern musical signal processing. Beginning with basic concepts, and leading to advanced applications, it covers such essential areas as sound synthesis (including detailed studies of physical modelling and granular synthesis) ,control signal synthesis, sound transformation (including convolution), analysis/resynthesis (phase vocodor, wavelets, analysis by chaotic functions), object-oriented and artificial intelligence representations, musical interfaces and the integration of signal processing techniques in concert performance.

Compiled by an international array of musical and technical specialists, this book deals with some of the most important topics in modern musical signal processing. Beginning with basic concepts, and leading to advanced applications, it covers such essential areas as sound synthesis (including detailed studies of physical modelling and granular synthesis) ,control signal synthesis, sound transformation (including convolution), analysis/resynthesis (phase vocodor, wavelets, analysis by chaotic functions), object-oriented and artificial intelligence representations, musical interfaces and the integration of signal processing techniques in concert performance.

This book serves as an ideal starting point for newcomers and an excellent reference source for people already working in the field. Researchers and graduate students in signal processing, computer science, acoustics and music will primarily benefit from this text. It could be used as a textbook for advanced courses in music signal processing. Since it only requires a basic knowledge of signal processing, it is accessible to undergraduate students.

This textbook provides both profound technological knowledge and a comprehensive treatment of essential topics in music processing and music information retrieval. Including numerous examples, figures, and exercises, this book is suited for students, lecturers, and researchers working in audio engineering, computer science, multimedia, and musicology. The book consists of eight chapters. The first two cover foundations of music representations and the Fourier transform—concepts that are then used throughout the book. In the subsequent chapters, concrete music processing tasks serve as a starting point. Each of these chapters is organized in a similar fashion and starts with a general description of the music processing scenario at hand before integrating it into a wider context. It then discusses—in a mathematically rigorous way—important techniques and algorithms that are generally applicable to a wide range of analysis, classification, and retrieval problems. At the same time, the techniques are directly applied to a specific music processing task. By mixing theory and practice, the book’s goal is to offer detailed technological insights as well as a deep understanding of music processing applications. Each chapter ends with a section that includes links to the research literature, suggestions for further reading, a list of references, and exercises. The chapters are organized in a modular fashion, thus offering lecturers and readers many ways to choose, rearrange or supplement the material. Accordingly, selected chapters or individual sections can easily be integrated into courses on general multimedia, information science, signal processing, music informatics, or the digital humanities.

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.