| 1 | Understand the elements of hypothesis testing |
| 2 | Understand the approach for Bayesian, minimax, Neyman-Pearson and composite hypothesis testing methods |
| 3 | Understand signal detection in discrete time, sequential detection, nonparametric and robust detection |
| 4 | Learn least squares, maximum likelihood, MAP and Bayesian parameter estimation |
| 5 | Learn detection and estimation of known signals in white and colored Gaussian noise |
| 6 | Understand multiuser detection |
| 7 | Understand optimum multiuser detector |
| 8 | Learn Decorrelating detector, non decorrelating linear multiuser detection |
| 9 | Understand decision driven detectors |