This book offers an introduction to digital signal processing (DSP) with an emphasis on audio signals and computer music. It covers the mathematical foundations of DSP, important DSP theories including sampling, LTI systems, the z-transform, FIR/IIR filters, classic sound synthesis algorithms, various digital effects, topics in time and frequency-domain analysis/synthesis, and associated musical/sound examples. Whenever possible, pictures and graphics are included when presenting DSP concepts of various abstractions. To further facilitate understanding of ideas, a plethora of MATLAB (R) code examples are provided, allowing the reader tangible means to "connect dots" via mathematics, visuals, as well as aural feedback through synthesis and modulation of sound. This book is designed for both technically and musically inclined readers alike-folks with a common goal of exploring digital signal processing.

This book is comprised of two parts - topics concerning research and development of an artificial system for automatic musical instrument timbre recognition and musical compositions. The technical part includes a detailed record of developed and implemented algorithms for feature extraction and pattern recognition. A review of existing literature introducing historical aspects surrounding timbre research, problems associated with a number of timbre definitions, and highlights of selected research activities in this field are also included. The developed timbre recognition system follows a bottom-up, data-driven model that includes a pre-processing module, feature extraction, and a Radial/Elliptical Basis Function neural network-based pattern recognition module. Significant emphasis has been put on feature extraction development for robust and consistent feature vectors for pattern recognition. The compositional part of the essay includes brief introductions to "A d'Ess Are," "Aboji," "48 13 N, 16 20 O," and "pH-SQ."