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  Nov 22, 2017
 
 
    
2017-2018 Catalog

Computer Engineering, M.S.


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Major Code: 8040 Degree Awarded: Master of Science
Delivery Mode(s): Classroom Age Restriction: No
Admission Status: Graduate Location(s): Main Campus - Melbourne
Admission Materials: GRE

The computer engineering program is committed to excellence in teaching, innovative and challenging research programs, and providing opportunities for the student’s development of professional engineering competence and scholarly achievement. A commitment to innovative research stimulates an excellent teaching and research program that allows graduates to use imaginative solutions to engineering problems. The program offers opportunities for graduates to pursue positions in research and development laboratories, industry and government.

Degree Requirements

The Master of Science in Computer Engineering is offered with both thesis and nonthesis options. Each requires a minimum of 30 semester credit hours of approved graduate study; however, course choices vary considerably depending on the student’s area of interest. Before completing nine semester credit hours, a student must submit for approval a master’s degree program plan to indicate the specialization chosen and the specific courses to be taken. Up to six credit hours of thesis may be included in the 30-credit-hour requirement. A nonthesis candidate must successfully pass the master’s final program examination and complete six credit hours of elective courses. The master’s final program examination measures the student’s understanding of topics in the core courses.

The curriculum includes areas of specialization in embedded systems, machine intelligence, mobile and wireless networking and speech recognition.

Curriculum


To earn the Master of Science in Computer Engineering, students are required to complete three core courses (nine credit hours), five specialization courses for 15 semester credit hours (may substitute approved electives), and six semester credit hours of thesis or approved electives.

A student may choose courses from one of the specializations below or meet with a faculty advisor to create a program plan.

Embedded Systems (9 credit hours)


The embedded systems specialization focuses on engineering of hardware/software systems. The educational program provides students with the necessary skills to unify hardware and software engineering, spanning microprocessor-based systems, system-on-chip design, parallel and distributed systems and resource-constrained devices. Special emphasis is placed on development of large-scale, secure and dependable real-time systems. The following courses must be taken in addition to the core courses.

Machine Intelligence (9 credit hours)


The machine intelligence (Ml) specialization focuses on models and computational methods for automated inference and reasoning, and applications of Ml in real-world application domains. The specialization area is structured in a manner that provides the necessary theoretical foundations of models, such as support vector machines, neural networks and other probabilistic models, and their associated learning algorithms; and the applications of such models and techniques in a variety of domains with a particular emphasis on speech recognition, among others. The following courses must be taken in addition to the core courses.

Embedded and Wireless Networking (9 credit hours)


The embedded and wireless networking specialization focuses on computer networking and communications for a variety of systems including next-generation wireless local- and wide-area networks, ad hoc and sensor networks, and specialty networks (satellite, avionic). Particular emphasis is placed on networking aspects including medium access control, routing and transport protocols; quality of service, energy efficiency and mobility management; and security and applications for intelligent and resource-constrained embedded network devices. The following courses must be taken in addition to the core courses.

Speech Recognition (9 credit hours)


The speech recognition (SR) specialization introduces students to techniques for speech recognition and language modeling used in the rapidly developing field of automatic speech recognition and natural language processing. Advanced SR topics include acoustic-phonetic modeling, robust speech recognition, processing paralinguistic information and multimodal processing. In addition, the specialization area examines most modern aspects of modern natural language theory, such as probabilistic modeling of pronunciation and spelling, probabilistic parsing and semantic analysis, among others. The following courses must be taken in addition to the core courses.

Program for Graduates from Other Fields


A student admitted to this program is expected to have a bachelor’s degree from a regionally accredited institution or the equivalent, with an undergraduate major in an engineering discipline, mathematics or the physical sciences, and an academic and/or professional record indicating a high probability of success in graduate work. Preparatory courses required to provide a student with the background necessary for successful graduate study in computer engineering are listed below. Depending on the individual’s background, other courses (e.g., differential equations and linear algebra) may also be required. Proficiency in these areas may be demonstrated by either successful course completion or by passing an equivalency examination. When possible, a student will be notified of deficiencies at the time of acceptance. In addition to the preparatory work described, all degree requirements listed above for the master of science degree must be fulfilled.

Total Credits Required: 30


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