BIOENG 1580 Syllabus - University of Pittsburgh

Course outline: (tentative/approximate, except for exam dates and due dates)
Week Topics
1. (8/31,9/2) Intro & overview of course. Review of continuous-time linear time-invariant (LTI) systems
theory: impulse and step response, convolution, input-output differential equation description, Fourier,
Laplace, frequency response, transfer function, close-loop (feedback) control systems.
2. (9/7,9) LTI rvw, cont’d. From continuous- to discrete-time: sampling and Nyquist criterion; aliasing and
anti-alias filters: the Butterworth LPF, design specifications for desired attenuation at Nyquist.
3. (9/15,16) From continuous to discrete: Difference equations; linear shift-invariant (LSI) discrete time
systems; the z-transform. LSI system transfer functions
4. (9/21,23) Z transform, cont’d. finite-impulse response (FIR) and infinite-impulse response (IIR)
systems. Inverse systems; All-pole (AR) & all-zero (MA) systems.
5. (9/28,30) Z-transform, cont’d. Converting from s-domain to z-domain and vice versa. Forward and
backward rectangular rule; bilinear transform; impulse invariance. Control systems. Matlab project 1
assigned 9/30: Human balance and postural control.
6. (10/5,7) Discrete Fourier analysis: Frequency response, DTFT, DFT, relations to FT.
7. (10/12,14) [No class 10/12 – Monday classes instead.] Discrete Fourier analysis, cont’d. Matlab project
1 due 10/14.
8. (10/19,21) Enhancing / detecting signals in noise: ensemble averaging; filtering; correlation; the
matched filter.
9. (10/26,28) MIDTERM Tues. 10/26. Signal enhancement / detection, cont’d; Matlab project 2 assigned
10/28.
10. (11/2,4) Intro to random signals. Wide-sense stationary signals. Autocorrelation, power spectral density.
Spectral estimation (non-parameteric): periodogram, Welch’s method, windowing.
11. (11/9,11) Spectral estimation, cont’d: parametric AR spectral estimation. Matlab project 2 due 11/11.
12. (11/16,18) Guest lectures by Prof. Aaron Batista, on neural signal processing: spike sorting, pattern
recognition.
13. (11/23) Nonlinear filtering: median and order-statistic filters, applied to eye movement data. Matlab
project 3 assigned 11/23: filtering eye movement (and/or skin blood flow) data.
14. (11/30, 12/2) Order-statistic filters, cont’d. Time-varying spectral analysis: the short-time Fourier
transform (STFT) and spectrogram
15. (12/7,9) Matlab project 3 due 12/7. STFT, spectrogram cont’d. Course wrap-up: Q&A, review.
16. (12/16) FINAL EXAM, Thursday 12/16, 12:00-1:50pm, in classroom (G24)