Computer, Digital, and Mathematical Music
Reference documents in Computer, Digital, and Mathematical Music.
Documents in Computer, Digital, and Mathematical Music
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Computer music is the applications of computing technology in music composition. It includes the theory and application of new and existing technologies and basic aspects of music, such as sound synthesis, digital signal processing, sound design, sonic diffusion, acoustics, and psychoacoustics.
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This book is intended as a user-friendly introduction to music and computers for college and upper-division secondary students. By organizing a presentation around interactive visual and sonic examples, we hope to provide a resource and guide for those just beginning to look at the field of computer music, as well as for more advanced computer composers who might benefit from a fresh insight.
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This book chronicles the history of Center for Computer Research in Music and Acoustics (CCRMA), tracing its origins in Stanford's Artificial Intelligence Laboratory through its present-day influence on Silicon Valley and digital music groups worldwide.
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There are strong links between music and mathematics dating back to Pythagoras and beyond. This book draws together the two disciplines outlining the key methods and concepts that underpin the subjects from one of the earliest uses of a musical cryptogram to computer music in the twenty-first century.
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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.
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This book explores the fundamentals of computer music and functional programming through the Haskell programming language. Functional programming is typically considered difficult to learn. This introduction in the context of creating music will allow students and professionals with a musical inclination to leverage their experience to help understand concepts that might be intimidating in more traditional computer science settings.
