Course Spotlight - Winter 2027

Instructor: Walter J. Kozacky Ph.D.

Schedule: Winter 2027, Tuesday 5:40pm - 7:30pm

Course Description:

The goal of this course is to incorporate the fundamental concepts and algorithms of Digital Signal Processing (DSP) to develop both real-world and real-time digital audio applications. We will cover fundamental DSP concepts, git version control, time and frequency domain processing , and adaptive filtering , including machine learning applications for digital audio. (2 units)

After completion, students should:

• Understand spectral audio processing, including the DFT, FFT, STFT, and their uses.
• Understand Adaptive Filtering for echo cancellation and interference removal in audio applications.
• Understand digital processing of analog signals, including sampling, quantization, number formats, git version control, time and frequency domain processing, including both o -line and real-time applications.
• Apply Machine Learning techniques to audio signal processing.

Course Topics: 

• DSP basics, Time and Frequency Domain response, z-Domain, FIR and IIR Filter implementation, windowing
• Numerical representation and Quantization, SNR, PCM/CD and wav file formats, digital audio formats Sampling
• Reconstruction, FIR and IIR filter design, biquad configurations
• STFT Short Term Fourier Transform, Spectrograms, Signal Classification, MEL/Bark bands
• Adaptive Filtering , Echo Cancellation, Interference removal
• Machine Learning for Audio, Neural networks, Gradient Descent and back propagation
• DSP Applications

Prerequisites: ECEN 233 or ECEN 133 (Digital Signal Processing I), and preferably ECEN 234 (Digital Signal Processing II).

Department Updates

Dragoslav Siljak, Professor Emeritus of Electrical Engineering, passed away on November 16. The Department of Electrical and Computer Engineering remembers him fondly, and would like to recognize his full life and his many gifts.