DSP Related Courses at Virginia Tech

These courses are compiled here for students, both undergraduate and graduate, who are interested in studying / researching in the field of Digital Signal Processing

Core DSP Courses

The following courses are the main DSP-related courses, and their prerequisite signals-and-systems courses, offered by the ECE department. Incoming graduate students are advised to start with ECE 4624.

ECE 2704 — Signals and Systems

Description
Analysis techniques for signals and systems. Signal representation, including Fourier and LaPlace transforms. System definitions and properties, such as linearity, causality, time invariance, and stability. Use of convolution, transfer functions and frequency response to determine system response. Applications to circuit analysis.

ECE 3704 — Continuous and Discrete Systems

Description
Continuous- and discrete-time system theory. Block diagrams, feedback, and stability theory. System analysis with Bode diagrams. Discrete-time stability, difference equations, Z-transforms, transfer functions, Fourier transforms, and frequency response. Sampling of continuous systems and an introduction to digital filtering.

ECE 4624 — Digital Signal Processing and Filter Design

Description
Analysis, design, and realization of digital filters. Discrete Fourier Transform algorithms, digital filter design procedures, coefficient quantization, finite wordlength arithmetic, fixed point implementation, limit cycles, noise shaping, decimation and interpolation.

ECE 5620 — Advanced DSP and Filter Design

Description
Advanced analysis, design, and realization of digital filters. Efficient Discrete Fourier Transform algorithm implementations, finite wordlength arithmetic, fixed point implementation, limit cycles, noise shaping, decimation and interpolation, multi-rate digital filter design, Hilbert transformers, analytic signal generation, basic adaptive filtering.

ECE 5624 — Wavelets, Filter Banks, and Applications

Description
Advanced digital signal processing topics. Review of filter design from a matrix perspective; relationship of time, frequency, and scale; downsampling, upsampling and multirate signal processing systems; quadrature mirror filters (QMF) and subband coding, bi-orthogonal and orthogonal filter banks; multiresolution analysis; wavelet basis construction and the cascade algorithm; wavelet representation of signals and Mallat's fast wavelet algorithm; and applications of wavelets and filter banks.

ECE 6624 — Spectral Estimation and Modeling

Description
An advanced introduction to the processing and modeling of random discrete-time signals. Random time series, auto- and cross-correlation sequences and their generation, filtering of random sequences, Wiener filters, matched filters, modeling assumption errors, one-step predictors, rational modeling of random sequences, parametric and non-parametric spectral estimation.

Related ECE Courses

The following list of courses are related ECE courses that DSPRL students have taken in the past.

ECE 4634 — Analog and Digital Communications

ECE 4654 — DSP Implementation of Communication Systems

ECE 5605 — Stochastic Signals and Systems I

ECE 5606 — Stochastic Signals and Systems II

ECE 5644 — Optimal Discrete Time Filtering

ECE 5654 — Digital Communications

ECE 5704 — Linear Systems Theory

ECE 5714 — Robust Estimation and Filtering

ECE 5724 — Neural and Fuzzy Systems

ECE 6604 — Advanced Topics in Communications

For example, depending on requests received, this course could be on speech processing, or on adaptive filtering, or on sensor array signal processing.

ECE 6714 — System Identification