This table provides information about both the lecture (L) and recitation (R) sessions.
| SES # | TOPICS | KEY DATES |
|---|---|---|
| R0 | Warming up. | |
| L1 | Introduction and overview. Linear, time-invariant (LTI) systems. | |
| R1 | Discrete-time Fourier transforms (DTFT), continuous-time Fourier transforms (CTFT): definitions and operations. | |
| L2 | Classes of DTFT, CTFT; energy spectral density. | |
| R2 | Spectral factorization. | |
| L3 | Sampling, interpolation, discrete-time (DT) processing of continuous-time (CT) signals. | |
| R3 | Fractional delay in DT systems. | Problem set 1 due |
| L4 | Group delay. | |
| L5 | State-space models. | |
| R4 | Obtaining state-space models. | Problem set 2 due |
| L6 | Equilibria and linearization. Modes of LTI state-space models. | |
| R5 | Linearization, eigenvalues, eigenvectors, modes. | |
| L7 | Reachability, observability, hidden modes, minimality. | |
| R6 | Reachability, observability, hidden modes. | Problem set 3 due |
| L8 | State observers and feedback. | |
| R7 | Observers and feedback. | |
| L9 | Observer-based feedback; DT control of CT systems. | |
| R8 | Probability review. | Problem set 4 due |
| L10 | Minimum mean-square-error (MMSE) and linear MMSE (LMMSE) estimation; orthogonality. | |
| R09 | MMSE and LMMSE estimation. | |
| L11 | Random processes, wide-sense stationarity (WSS). | |
| R10 | Correlation/covariance functions. | Problem set 5 due |
| L12 | Ergodicity. LMMSE prediction from finite data. | |
| Quiz 1 | ||
| L13 | LTI filtering of WSS processes. | |
| R11 | LTI filtering of WSS processes. | |
| L14 | Power spectral density (PSD). | |
| R12 | PSD. Modeling and whitening filters. | |
| L15 | Unconstrained (noncausal) Wiener filtering. | |
| R13 | Unconstrained Wiener filtering. | Problem set 6 due |
| L16 | Oversampled noise modulation. | |
| R14 | More PSD and Wiener filter practice. | |
| L17 | Pulse-amplitude modulation (PAM); Nyquist condition for zero intersymbol interference (ISI). | |
| R15 | PAM. Nyquist condition. | Problem set 7 due |
| L18 | Binary PAM, hypothesis testing, minimum probability of error. | |
| R16 | Optimal detection, false alarm, miss. | |
| L19 | Likelihood ratio; Neyman-Pearson detection. | |
| R17 | Receiver operating characteristic (ROC). | Problem set 8 due |
| L20 | Quadrature amplitude modulation (QAM); modems. | |
| Quiz 2 | ||
| L21 | Signal detection in white Gaussian noise. | |
| R18 | Matched filtering. | |
| L22 | Pulse compression. | |
| R19 | Signal detection in colored noise. | Problem set 9 due |
| L23 | (Causal) Wiener prediction. | |
| R20 | Wiener prediction. | |
| L24 | Spectral estimation, periodogram averaging. | |
| R21 | Review. | Problem set 10 due |
| L25 | Notions of information theory and coding. | |
| R22 | Review. | |
| L26 | Clinical monitoring, estimation and prediction. |