EE623: Advanced Signal Processing

1. Overview of Basic DSP and Random Process: Convolution sum, Finite (FIR) and Infinite (IIR) Impulse Responses, Difference equations, Discrete-time Fourier transform (DTFT) and its properties, Random Signals,  Z-transform (ZT) and its properties.
2. Signal Modeling: Least Square Method, Pade Approximation, Prony’s Method, Finite Date Records, Stochastic Models (ARMA, AR and MA).
3. The Levinson Recursion: The  Levinson-Durbin Recursion, Lattice Filters.
4. Optimum Filters: The FIR Wiener Filter, Filtering, Linear Prediction, Noise Cancellation.
5. Spectrum Estimation: Nonparametric Methods , Minimum Variance Spectrum Estimation, Maximum Entropy Methods, Parametric Methods, Frequency Estimation.