ECE 315 - Signal Processing Methods



Lectures: Prof. Marco F. Duarte, Marcus Hall 215I,
Office Hours: Tuesdays and Thursdays 10:30am-11:30am (or by e-mail appointment)

Teaching Assistant:
Shivakumar Valpady, Office Hours TBA


Lectures: 10:10am-11:00am Monday, Wednesday, Friday @ 20 Goessman Lab.


This course focuses on the study of discrete-time signals and linear discrete-time systems. It constitutes the basic theory behind a further study of digital communication theory and systems, digital control theory and systems, digital signal and image processing, networking, and almost all disciplines of electrical and computer engineering.


ECE 213: Continuous-Time Signals and Systems.

ECE 214: Probability and Statistics.


We will use two textbooks that are available online for download at no cost and in physical version at low cost:

  1. Signals and Systems: Theory and Applications” by F. Ulaby and A. Yagle (can be purchased for ~$70).

  2. Introduction to Probability, Statistics, and Random Processes” by H. Pishro-Nik (can be purchased for ~$30).

  3. H. Hsu, “Signals and Systems,” Schaum’s Outline Series, McGraw Hill, 2010: provides a significant number of examples and exercises for exam preparation at a low cost.


Week 1: Discrete-time signals; review of basic signals, signal operations and properties.

Week 2: Discrete-time system properties: causality, stability, linearity, time invariance. Eigenfunctions of discrete-time LTI systems.

Week 3: Time domain analysis of discrete-time systems: impulse response, convolution, difference equation representations.

Week 4: Z Transform. Properties and inversion. Partial fraction expansions.

Week 5: Filter design and stability. Frequency response.

Week 6: Fourier Series representations of periodic discrete-time signals. Discrete-Time Fourier Transform.

Week 7: Discrete Fourier Transform and its application to discrete periodic signals. Fast Fourier Transform.

Week 8: Applications to system analysis: filter classifications, causality, deconvolution.

Week 9: ROC, Stability, and Causality.

Week 10: FIR and IIR Filter Design

Week 11: Multirate signal processing. Upsampling, downsampling, and interpolation.

Week 12: Review of basic concepts in probability. Random processes. Wide-sense stationary processes.

Week 13: Power Spectral Density. Random processes through LTI systems. Noise models. Noise in electronic systems.