University of Delaware - College of Engineering
ELECTRICAL & COMPUTER ENGINEERING

Online Master of Science in Electrical and Computer Engineering: Courses




Strengthen Your Skills in Data and Communications

The University of Delaware’s online Master of Science in Electrical and Computer Engineering is a non-thesis program that gives working engineers and recent graduates a broader foundation in signal processing and communications. Electrical and computer engineering courses combine the leading research in the field with real-world application to advance your training with the latest developments in the field.

Course Descriptions

ELEG 632 Mathematical Methods for Signal Processing
The application of mathematics to signal processing. Topics include, among others, applications of linear and matrix algebra, iterative and recursive methods, and optimization techniques. Example applications include: Karhunen-Loeve approximation, subspace techniques, steepest descent, expectation maximization and Hidden Markov Models, and Viterbi algorithm.
Prerequisites: Linear and matrix algebra and digital signal processing.

ELEG 634 Signals and Systems
Reviews basic concepts of discrete and continuous time signals, control systems, and linear algebra. Transforms, sampling, aliasing, linear algebra and systems of equations, matrix factorizations, eigenvalues and eigenvectors, least squares, and the Cayley-Hamilton theorem are studied.

ELEG 631 Digital Signal Processing
Theory of discrete-time signals and systems with emphasis on the frequency domain description of digital filtering and discrete spectrum analysis, fast Fourier transform, z-transform, digital filter design, relationship to analog signal processing.

ELEG 635 Digital Communication
The theory and applications of digital communications including modulation, pulse shaping, and optimum receiver design for additive white Gaussian noise and bandlimited channels.
Prerequisites: Undergraduate course in probability, signals and linear systems.

ELEG 636 Statistical Signal Processing
Introduction to random vectors and random processes and second-order moment and spectral characterizations. Linear transformations of stationary processes. Parameter estimation. Orthogonality principle and optimal linear filtering. Levison recursion and lattice prediction filters. AR and ARMA models and their Yule-Walker characterizations. Classical and modern spectrum estimation.
Prerequisites: Undergraduate courses in probability and signals and linear systems.

CISC 650/ELEG 651 Computer Networks
Foundation principles, architectures, and techniques employed in computer and communication networks. Focuses on mechanisms used in TCP/IP protocol suite. Topics include connection management, end-to-end reliable data transfer, sliding window protocols, quality of service, flow control, congestion control, routing, LANs, framing, error control, analog versus digital transmission, packet versus circuit switching, multiplexing.
Prerequisites: An undergraduate level course in computer architecture and operating systems.

CPEG 665 Introduction to Cybersecurity (CYBER I)
Introduction to computer and network security covers the foundation security policies and methods to provide confidentiality, integrity, and availability, as well as cryptography, auditing, and user security. Topics are reinforced with hands-on exercises run in a virtual machine environment.

CPEG 657 Search and Data Mining
With the increasing amount of textual information, it is important to develop effective search engines, such as Google, to help users manage and exploit the information. Examine the underlying technologies of search engines and get hands-on project experience. Requires good programming skills.

CPEG 672 Applied Cryptography
This cybersecurity course explores modern Cryptography covering algorithms and cryptosystems, cryptanalysis, and best practices for application and implementation of crypto in software systems.
Prerequisite: CPEG 665

ELEG 617 The Smart Grid
An examination and analysis of smart grid technologies, applications, and transformational impacts on the electric utilities. Topics cover smart grid fundamentals, objectives, technologies (power, communications and information), architectures, applications, evolution, and implementation challenges.

Course Schedule

The online electrical and computer engineering courses are 7 weeks long, with multiple entry points offered per calendar year. Course sessions are as follows: Spring 1, Summer and Fall 1. View our academic calendar.

Fill out the form to the right to receive more information about UD’s online M.S. in electrical and computer engineering courses.


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