Teaching

The lectures slides for the courses taught are available for download from this web-page as a PDF.

Advanced Signal Processing

  1. Lecture 1: Random Variables
  2. Lecture 2: ARMA Modeling
  3. Lecture 3: Estimation Theory
  4. Lecture 4: MVU Estimation
  5. Lecture 5: BLUE MLE
  6. Lecture 6: Least Squares
  7. Lecture 7: Adaptive Filters

Spectral Estimation and Adaptive Filtering

  1. Course Introduction
  2. Lecture 1: Spectral Estimation Introduction
  3. Lecture 2: Nonparametric SE
  4. Lecture 3: Modern SE
  5. Lecture 4: Adaptive SP
  6. Lecture 5: LMS Modifications
  7. Lecture 6: Complex Valued Adaptive Filters
  8. Lecture 7: Sequential Estimation
  9. Lecture 8: Blind Adaptive Filters (not required)

Digital Signal Processing

  1. Course Introduction and Background
  2. Lecture 1: Digital Filters: FIR and IIR
    1. Supplement to Lecture 1: FIR filters
    2. Supplement to Lecture 1: IIR Filters
    3. Supplement to Lecture 1: IIR Filters - Bilinear Transform
  3. Lecture 2: Basic Spectrum Estimation - DFT vs FFT and Their Relationship
    1. Supplement to Lecture 2: DFT, DTFT, and FFT
  4. Lecture 3: Linear Stochastic Modelling
  5. Lecture 4: Finite Wordlength Effects
  6. Lecture 5: Multirate DSP
    1. 5a: Theory
    2. 5B: Applications
  7. Lecture 6: Optimum_MSE_Filtering
  8. Lecture 7: MSE Estimation: Wiener filtering
  9. Lecture 8: Case Study: Prediction Problem
  10. Lecture 9: MSE Estimation: The Kalman filter