Discrete-time transforms - Z-transform - inverse transform by partial fraction expansion

Pencase: calculation autocorrelation function and PSD

Pencast: spectral factorization

Random processes

Random Vectors

Exercise2 1a Pencast

Linear Estimators: MVUE and BLUE

Derivation of the MLE for Linear Signal Model and AWGN

t-statistics for Hypothesis Testing

Numerical Methods for Solving Estimators

Introduction to Likelihood Function

Introduction to Binary Hypothesis Testing and Receiver Operating Characteristics

Introduction to Least Squares Estimation

Estimator Bias, Variance, CRLB

Bayesian Estimation: MAP and MMSE

Pencast: estimation AR model parameters

Spectral analysis: parametric methods

Non-parametric spectral estimation

Energy and power signal

Windowing and zero-padding

Spectral Factorization

Continuous random variables

LTI with random inputs

Special random processes

Random signal models