2012–2013 UNIVERSITY CATALOG - Florida Institute of Technology

Electrical Engineering, Ph.D. ___________________
major Code: 9042 Degree awarded: Doctor of Philosophy
age restriction: N admission status: graduate
Delivery mode/s: classroom only Location/s: main campus
admission materials: 3 letters of
recommendation, résumé, objectives
The doctor of philosophy degree is offered to students who want to
pursue advanced research in an area of existing faculty expertise.
The doctoral degree is granted in recognition of high achievement
in a program of study, required examinations and original research
in the field of electrical engineering.
Admission Requirements
Admission to doctoral study is granted to applicants who have
received master’s degrees in electrical engineering or related fields
from accredited institutions or from international institutions that
provide suitable preparation for doctoral-level studies.
Included with the application should be a short, clear statement of
the applicant’s interests and objectives. An on-campus interview is
highly recommended, although not required for admission.
General admission requirements and the process for applying are
presented in the Academic Overview section.
Degree Requirements
The degree of doctor of philosophy is conferred primarily in recognition
of creative accomplishment and ability to investigate
scientific or engineering problems independently, rather than for
completion of a definite course of study. The work will consist of
advanced studies and research leading to a significant contribution
to a chosen research area.
The doctoral program in electrical engineering may be completed
with a minimum of 48 credit hours beyond the master’s degree.
Each student must complete an approved program of study beyond
that required for a master’s degree, pass a comprehensive written
examination, complete a program of significant original research,
and prepare and defend a dissertation concerning the research. In
addition, to demonstrate the achievement of new knowledge in the
field, a publication in a professional journal of conference proceedings
is required.
General degree requirements are presented in the Academic
Overview section.
Coursework and Dissertation Summary
Doctoral coursework minimum beyond master’s degree ............................ 24
Doctoral research and dissertation............................................................. 24
TOTAL MINIMUM BEYOND THE MASTER’S DEGREE ................... 48
Curriculum
A minimum of 24 credit hours of coursework and at least 24 credit
hours of Dissertation Research (ECE 6999) beyond a master’s
degree are required. Up to nine credit hours outside of electrical
and computer engineering can be counted toward the degree.
The student’s adviser and the department head must approve a
program of study. A wide degree of latitude is allowed in course
selection and research interest within the capability of the university
and the student’s academic background. This requirement is
imposed at the discretion of the doctoral committee.
After admission to doctoral candidacy, a yearly seminar demonstrating
progress must be presented to the graduate faculty.
122 Florida Tech
RESEARch
Current areas of research include image processing,
electromagnetics, computer vision, neural networks, speech
processing, wireless communications and pattern recognition.
These activities are being carried out in relation to the following
general areas of research interest.
Electromagnetics: Applied and computational research is conducted
in order to manipulate electromagnetic fields. Antennas,
frequency selective surfaces, high impedance ground planes, and
bandgap structures are designed and analyzed using computational
tools, then tested for validation. The ability to model electromagnetic
properties of complex structures requires full-wave analysis
with finite element, method of moments or finite difference techniques.
RF measurements are conducted in the antenna laboratory
that houses an anechoic chamber and screen room.
Image processing: Much of the research is directed at basic problems
and contributes to the solution of major national problems
in vision and image processing. These include automated object
detection and perception, computer imaging, modeling and other
areas of image analysis. Techniques being used include traditional
techniques and others that include wavelets, fractals, higher-order
statistics and morphology. Application areas include autonomous
inspection in manufacturing and other commercial uses. Projects
include the fusion of infrared and visible imagery, and denoising of
imagery using advanced methods. In addition, many of the techniques
in image processing are being applied to speech processing.
Lightwave and Optronics Laboratories: The laboratories are
dedicated to research and development efforts in the field of optical
electronics such as optical communications and optical sensors.
Activities with regards to communication span the development
of state-of-the-art multi-Tb/s optical transmission architectures
to design and development of cryogenic instrumentation for the
space program. Current activities are focused on innovative optical
communications architectures such as spatial and orbital angular
momentum (OAM) photon-based, multiplexing in optical fibers. As
a result, revolutionary capabilities for future optical networks using
hybrid architectures have already started to emerge and several
multi-Tb/s optical systems employing multiple photon degrees of
freedom were recently reported. Sensor research includes 2-D and
3-D structural health monitoring of strain and material failure, and
environmental parameters. These laboratories are equipped with
instrumentation such as tunable lasers, optical spectrum analyzers,
bit error rate test sets, fiber amplifiers and digitally controlled
attenuators, optical time domain reflectometers, fiber splicers and
customized data processing systems for data acquisition and signal
processing.
Microelectronics Laboratory: See the Institution Overview section.
Signal processing: Research is performed in neural networks,
image processing, pattern recognition and speech processing.
Algorithms have been developed for near-real-time detection and
classification for several applications such as communications,
noise reduction, and speaker identification. Techniques being used
include traditional techniques and others that include wavelets,
fractals, higher-order statistics and morphology. Projects include
the analysis and classification of infrasound signals, development of
pattern recognizers, denoising of imagery and speech identification.