Instructor: |
Douglas L. Jones, 113 CSL, dl-jones at illinois Lectures: Monday, Friday, 10-11, Tuesdays 1:30-2:30 |
DIGITAL SIGNAL PROCESSING by Thomas J. Cavicchi. Particularly good conceptual explanations and figures describing all concepts, but not many examples how to do the computations.
ANALOG AND DIGITAL SIGNAL PROCESSING by Ashok Ambardar. Good overview of signals (Ch 2), Fourier series (Ch 5), Fourier Transform (Ch 6,7), DFT and spectral analysis (Ch 12), z-transform (Ch 13), pole/zeros (Ch 13), filter design (Ch 14).
DIGITAL SIGNAL PROCESSING: A COMPUTER SCIENCE PERSPECTIVE by Jonathan Y Stein. Particularly good on signals, Fourier series and Fourier transform, STFT, and z-transform.
Week | Date | Topics | Text |
---|---|---|---|
1 | Aug 22-26 | Overview; Period and frequency; Fourier Series | Lathi, Ch 6.1; Munson/Singer Notes 1.1-1.5 |
2 | Aug 29 - Sep 2 | Review of complex numbers; Exponential Fourier Series; Fourier Transform | Lathi, Ch B.1, B.2, 6.2, 6.3; Munson/Singer Notes 1.5-1.14 |
3 | Sep 5-9 | Fourier Transform and properties; impulse function | Lathi, Ch 7.1-7.4; Munson/Singer Notes 7.25-7.28 |
4 | Sep 12-16 | Fourier Transform properties; time-domain sampling and quantization overview | Lathi, Ch 7.1-7.4; Munson/Singer Notes 7.25-7.28 |
5 | Sep 19-23 | Discrete-Time Fourier Transform (DTFT) and properties | Proakis, Ch 4.1-4.3, 4.5; Munson/Singer Notes 2.1-2.18 |
6 | Sep 26-30 | Discrete Fourier Transform, properties, and spectrum analysis | Proakis, Ch 5,1-5.2, 5.4; Munson/Singer Notes 2.18-2.25, 3.1-3.10; An online module about DFT-based spectral analysis |
7 | Oct 3-7 | Spectrum analysis, Sampling theory (A/D and D/A, time and frequency analysis) | Proakis, 1.4 and 5.4; Munson/Singer Notes 3.1-3.10, 4.1-4.8 An online module about DFT-based spectral analysis |
8 | Oct 10-14 | Equivalent analog frequency response of a digital system. Discrete-time system theory: linearity, causality, shift-invariance, BIBO stability; convolution | Proakis, Ch 2.2.3-4, 2.3.2-6; Munson/Singer Notes Chapters 8.15-26, Ch 5. |
9 | Oct 17-21 | Difference equations. FIR and IIR impulse (filter) responses. Z-transform and properties (linearity, shift, convolution). Transfer function of general recursive difference equations. Poles and zeros. Frequency response from transfer function. | Proakis Ch 2.4, 3.1-3.3, 3.6.1, 3.6.3, 3.6.4, 4.2.6; Munson/Singer Notes Ch 6, 7.1-8 |
10 | Oct 24-28 | Notch filter design. Ideal filters. Standard IIR filter types. Generalized linear phase. | Proakis Ch 8.1, 8.3.5, 8.2.1; Munson/Singer Notes Chapter 8.1-15, Ch 10 |
11 | Oct 31-Nov 4 | Physiology and psychology of hearing (Prof. Robert Wickesberg) | |
12 | Nov 7-11 | Generalized linear phase. Window design of FIR filters. Parks-McClellan (minimax) FIR filters. | Proakis, Ch 8.2.1-2, 8.2.4 (overview); Munson/Singer Notes Ch 11 |
13 | Nov 14-18 | NO CLASS | |
Nov 21-25 | THANKSGIVING BREAK | ||
14 | Nov 28-Dec 2 | Image processing: 2-D signals. 2-D Fourier transforms and filtering. Edge detection. Projection-slice theorem. CT tomography, MRI. Wavelet transform. | Munson/Singer Notes, Chapter 15.1-7. |
15 | Dec 5-9 | Review |
Your assignment is to extend this code to make more interesting music. First, change the timbre of the sound by altering the Fourier series coefficients used to generate the underlying periodic signals. For example, you can make a sawtooth wave (similar to that of a violin) with the appropriate Fourier series coefficients. The current code only implements an exponential decay envelope; you are to make a more sophisticated envelope including a linear ramp-up "attack", a constant-level "sustain", then followed by the exponential decay. Make the duration of each part adjustable as in the current code, so that you can create interesting tunes. Finally, use your improved code to synthesize a different tune of at least five notes.
The short Frequency and Music online course will explain the relationships of frequency and harmonics to music and how to match musical pitches and intervals to frequencies.
Midterm Exam | 25% |
Final Exam | 35% |
Homework | 20% |
Matlab-based lab exercises | 20% |