Lectures

Tuesday, Thursday: 1:00-2:20, Martel 101

Class Schedule for Fall 2006
Week Topic HW
(Due Thursdays)
8/29

Class organization.
Probability: events, random variables, functions of random variables, probability functions, expected values, characteristic functions.
9/5

Probability: random vectors, correlation, the Gaussian random variable and the Gaussian random vector.
Random processes: Definitions, stationarity

2.2, 2.3, 2.4, 2.5
9/12 Random processes: Correlation functions and power spectra, filtering of processes, sampling processes, ergodicity, white noise. 2.8, 2.10, 2.12, 2.14, 2.16
9/19

Poisson processes.
Linear vector spaces.
Karhunen-Loève expansion.

 2.18, 2.19, 2.20, 2.26, 2.30
9/26 Optimization theory: Unconstrained and constrained problems. Quiz I Due
10/3 Estimation theory: Definitions, minimum mean squared error, maximum a posteriori, and linear estimation. 2.40, 4.1, 4.3, 4.10
10/10 Maximum likelihood estimation: Cramér-Rao bound, properties. 4.2, 4.4, 4.5, 4.7
10/17 Signal parameter estimation.
Linear signal estimation: Wiener filters.		  
10/24

Linear signal estimation: Wiener filters

 4.6, 4.13, 4.14, 4.19
10/31

Linear signal estimation: Kalman filters, adaptive filters

 Quiz II Due
11/7

Adaptive Filters.
Detection theory: likelihood ratio test, ROC curves.

 4.17, 4.23, 4.25, 4.28
11/14

Detection theory: M models, Neymann-Pearson detection, Stein's lemma

 5.1, 5.2, 5.4, 5.8
11/21 Detection theory: Sequential detection.  
11/28

Detection theory: Uncertainties in models

 5.11, 5.12 , 5.22, 5.42
12/3 Detection theory: Signals in additive noise
 Quiz III Due