Introduction to digital signal processing : computer musically speaking / Tae Hong Park.

Includes bibliographical references and index.

1. Acoustics, hearing limitations, and sampling. 1. Introduction. 2. The sine tone. 3. Human hearing and its limitations. 4. Sampling : the art of being discrete. 5. Quantization and Pulse Code Modulation (PCM). 6. DC component. 7. Distortion and square waves. 8. Musical examples -- 2. Time-domain signal processing I. 1. Introduction. 2. Amplitude envelope and ADSR. 3. Wavetable synthesis. 4. Windowing, RMS, and amplitude envelope. 5. Time-domain fundamental frequency computation. 6. Sample rate conversion. 7. Overlap and Add (OLA). 8. Musical examples -- 3. Time-domain processes II. 1. Introduction. 2. Granular synthesis. 3. Amplitude distortion and waveshaping. 4. Some familiar time-domain DSP effects. 5. Musical examples -- 4. Sine waves. 1. Introduction. 2. Sinusoids revisited. 3. Imaginary, complex numbers, and Euler's formula. 4. Sinusoidal modulation techniques I : amplitude. 5. Sinusoidal modulation techniques II : frequency. 6. Musical examples -- 5. Linear time-invariant systems. 1. Introduction. 2. Difference equations : starting with the moving average algorithm. 3. Linear-Time Invariant (LTI) systems. 4. Impulse response. 5. Convolution. 6. System diagrams and digital building blocks. 7. Musical examples -- 6. Frequency response. 1. Introduction. 2. The frequency response. 3. Phase response and phase distortion. 4. The (almost) magical Z-transform. 5. Region of Convergence (ROC). 6. Stability and the unit circle. 7. The inverse z-transform. 8. Useful tools in MATLAB. 9. Musical examples -- 7. Filters. 1. Introduction. 2. Low/high/band-pass and band-stop filters. 3. Filter examples. 4. Musical examples -- 8. Frequency-domain and the Fourier transform. 1. Introduction. 2. Additive synthesis. 3. The Fourier transform. 4. The Discrete-Time Fourier Transform (DTFT) and the Discrete Fourier Transform(DFT). 5. Short-Time Fourier Transform (STFT). 6. Zero padding. 7. Aliasing revisited. 8. Another look : down-sampling and up-sampling revisited. 9. Windowing revisited : a view from the frequency-domain side. 10. The Fast Fourier Transform (FFT). 11. Convolution (also) revisited. 12. One more look at dithering. 13. Spectogram. 14. Fourier transform properties and summary. 15. MATLAB and Fourier transform. 16. Musical examples -- 9. Spectral analysis, vocoders, and other goodies. 1. Introduction. 2. Spectral analysis. 3. Vocoders (voice coders). 4. Research topics in computer music. 5. Musical examples.

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 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

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