CONTENTS -- Preface -- Acknowledgements -- About the Book Cover Design -- 1. Acoustics, Hearing Limitations, and Sampling -- 1 Introduction -- 2 The Sine Tone -- 3 Human Hearing and Its Limitations -- 3.1 Duration -- 3.2 Pitch -- 3.3 Amplitude and sound levels -- 3.3.1 Sound intensity level (SIL) -- 3.3.2 Sound pressure level (SPL) -- 3.3.3 Just noticeable di.erence (JND) -- 3.3.4 Equal loudness curve -- 3.4 Auditory masking -- 4 Sampling: The Art of Being Discrete -- 4.1 Sampling theorem -- 4.2 Aliasing -- 5 Quantization and Pulse Code Modulation (PCM) -- 5.1 SNR and QSNR -- 6 DC Component -- 7 Distortion and SquareWaves -- 7.1 Dithering -- 8 Musical Examples -- References and Further Reading -- 2. Time-Domain Signal Processing I -- 1 Introduction -- 2 Amplitude Envelope and ADSR -- 3 Wavetable Synthesis -- 4 Windowing, RMS, and Amplitude Envelope -- 4.1 Windowing:More details -- 4.2 RMS and amplitude envelope -- 5 Time-Domain Fundamental Frequency Computation -- 5.1 Zero-crossing rate -- 5.2 Autocorrelation -- 5.3 Cross-correlation -- 6 Sample Rate Conversion -- 6.1 Up-sampling -- 6.2 Down-sampling -- 7 Overlap and Add (OLA) -- 7.1 OLA: Problems and solutions -- 8 Musical Examples -- References and Further Reading -- 3. Time-Domain Processes II -- 1 Introduction -- 2 Granular Synthesis -- 2.1 Basic granular synthesis parameters -- 2.2 Asynchronous granular synthesis -- 2.3 Pitch shifting and time stretching/compression -- 2.4 Sound morphing with granular synthesis -- 3 Amplitude Distortion and Waveshaping -- 3.1 Dynamic compressor -- 3.2 Distortion -- 3.3 Dynamic expander -- 3.4 Tape saturation -- 3.5 Waveshaping synthesis -- 3.5.1 Chebychev polynomials of the 1st kind -- 4 Some Familiar Time-Domain DSP Effects -- 4.1 Equal power panning -- 4.2 Delays -- 4.2.1 Echo, chorus, and flanging -- 5 Musical Examples -- References and Further Reading.

4. Sine Waves -- 1 Introduction -- 2 Sinusoids Revisited -- 3 Imaginary, Complex Numbers, and Euler's Formula -- 3.1 Euler's formula -- 4 Sinusoidal Modulation Techniques I: Amplitude -- 4.1 Beating -- 4.2 Amplitude modulation and ring modulation -- 4.3 Amplitude modulation (AM) -- 4.4 Ring modulation -- 4.4.1 Ring modulation with complex signals -- 5 Sinusoidal Modulation Techniques II: Frequency -- 5.1 FM: Sidebands and the Bessel function -- 5.2 Modulation index -- 5.3 General topics in FM control parameters -- 6 Musical Examples -- References and Further Reading -- 5. Linear Time-Invariant Systems -- 1 Introduction -- 2 Difference Equations: Starting with the Moving Average Algorithm -- 2.1 Causality -- 2.2 Difference equations: General form -- 3 Linear-Time Invariant (LTI) Systems -- 3.1 Linearity property: Scalability and superposition -- 3.2 Time-invariance property: Time-shift invariance -- 3.3 Importance of LTI systems in DSP -- 4 Impulse Response -- 4.1 Finite impulse response (FIR) and infinite impulse response (IIR) -- 4.2 Stability and IIR systems -- 5 Convolution -- 5.1 Convolution "Need to Knows" -- 6 System Diagrams and Digital Building Blocks -- 7 Musical Examples -- 6. Frequency Response -- 1 Introduction -- 2 The Frequency Response -- 2.1 Characteristics and properties of H(ejθ) -- 2.1.1 Frequency range and Nyquist revisited -- 2.1.2 H(ejθ) and periodicity property -- 2.1.3 Symmetry -- 2.2 More stuff on the frequency response -- 3 Phase Response and Phase Distortion -- 3.1 Phase delay -- 3.2 Linearity and phase -- 3.3 Phase response and continuous phase -- 3.4 Group delay -- 4 The (Almost) Magical Z-Transform -- 4.1 What does all this mean? Part I -- 4.2 What does all this mean? Part II: poles and zeros -- 4.3 What does all this mean? Part III: the unit circle and the z-plane -- 4.4 More "complex" systems.

5 Region of Convergence (ROC) -- 5.1 Causal system ROC. -- 5.2 Mixed-causality systems -- 5.3 ROC summary -- 6 Stability and the Unit Circle -- 7 The Inverse Z-Transform -- 7.1 Long division method -- 7.2 Taylor series expansion method -- 7.3 Contour integration/residue theorem method -- 8 Useful Tools in MATLABR -- 9 Musical Examples -- References and Further Reading -- 7. Filters -- 1 Introduction -- 2 Low/High/Band-Pass and Band-Stop Filters -- 2.1 Filter design specifications -- 2.2 Passband, stopband, and transition band -- 2.3 Cutoff frequency -- 2.4 Filter order, filter sharpness, and ripple -- 2.5 MATLABR filter design tools -- 3 Filter Examples -- 3.1 Subtractive synthesis and filters -- 3.2 Bi-quadratic filter (a.k.a. Bi-quad filter) and theWah-Wah filter -- 3.3 The Comb-filter -- 3.3.1 Comb-filter interpretation -- 3.3.2 Comb-filter examples -- 3.4 String vibration and standing waves -- 3.5 Physical modeling synthesis and the plucked stringmodel -- 3.5.1 Direct implementation of di.erence equations -- 3.6 Phase as a filtering application -- 3.6.1 The chorus effect -- 3.6.2 Multi-tap filters and filter banks -- 3.6.3 Fractional delay -- 3.6.4 The flanger effect -- 3.6.5 The all-pass filter -- 3.6.6 Very basic all-pass filter reverb -- 4 Musical Examples -- References and Further Reading -- 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) -- 4.1 Magnitude, Phase, and Other Basic Properties of the DFT -- 4.2 Time Resolution vs. Frequency Resolution in DFTs -- 5 Short-Time Fourier Transform (STFT) -- 6 Zero Padding -- 7 Aliasing Revisited -- 8 Another Look: Down-Sampling and Up-Sampling Revisited -- 8.1 Down-Sampling -- 8.2 Up-Sampling.

9 Windowing Revisited: A View from the Frequency-Domain Side -- 9.1 Rectangular Window -- 9.2 Hann Window -- 9.3 Hamming Window -- 9.4 Blackman Window -- 9.5 Chebychev and Kaiser Windows -- 9.6 Not Just More Windowing Stuff -- 10 The Fast Fourier Transform (FFT) -- 11 Convolution (also) Revisited -- 11.1 Circular Convolution and Time-Aliasing -- 12 OneMore Look at Dithering -- 13 Spectrogram -- 14 Fourier Transform Properties and Summary -- 15 MATLABR and Fourier Transform -- 16 Musical Examples -- References and Further Reading -- 9. Spectral Analysis, Vocoders, and other Goodies -- 1 Introduction -- 1.1 Musical signals and important nomenclatures -- 2 Spectral Analysis -- 2.1 Long-term average spectrum (LTAS) -- 2.2 Log vs. linear -- 2.3 Spectral peaks, valleys, and spectral envelope -- 2.4 Extraction of fundamental frequency and harmonics -- 2.4.1 Inverse comb-filtering -- 2.4.2 Cepstrum analysis -- 2.4.3 Harmonic product spectrum -- 3 Vocoders (Voice Coders) -- 3.1 Channel-vocoder -- 3.1.1 Filter banks, envelope followers, and the encoder -- 3.1.2 Voiced and unvoiced analysis and the decoder -- 3.1.3 Voiced and unvoiced decision-making -- 3.1.3.1 Zero-crossing analysis -- 3.1.3.2 Pre-emphasized energy ratio -- 3.1.3.3 Low-band to full-band energy ratio -- 3.1.3.4 Spectral flatness measure -- 3.2 Linear predictive coding (LPC) -- 3.3 LPC coefficient computation -- 3.4 The phase vocoder -- 3.4.1 Estimation of instantaneous frequency -- 3.4.2 Phase unwrapping -- 3.4.3 Phase vocoder: Filter-bank interpretation -- 3.4.4 Phase vocoder: Fourier transform interpretation -- 3.4.5 Phase vocoder basics: Time and pitch-shifting -- 3.4.5.1 Time-shifting -- 3.4.5.2 Pitch-shifting -- 4 Research Topics in Computer Music -- 4.1 Salient feature extraction -- 4.1.1 Spectral envelope -- 4.1.2 Spectral centroid -- 4.1.3 Shimmer and Jitter -- 4.1.4 Spectral flux.

4.1.5 Log spectral spread -- 4.1.6 Roll-off -- 4.1.7 Attack time (rise time) -- 4.1.8 Amplitude modulation (Tremolo) -- 4.1.9 Temporal centroid -- 4.2 MIR (Music information retrieval) -- 4.2.1 Query-by-humming (QbH) -- 4.2.2 Automatic beat detection and rhythm analysis -- 4.2.3 Automatic timbre recognition -- 4.3 FMS (feature modulation synthesis) -- 5 Musical Examples -- References and Further Reading -- Appendix -- 1 To Scale or Not to Scale: That is the Question -- 1.1 Equal temperament scale -- 1.2 Just intonation -- 1.3 Bark scale -- 1.4 Mel scale -- 2 MATLAB Programs Used in This Book -- References and Further Reading -- Index.