This table provides information about both the lecture (L) and recitation (R) sessions.

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.  

Course Info

Learning Resource Types

grading Exams with Solutions
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