Introduction
to Acoustics (AM 520)
Prof. Robin Cleveland
- Graduate
Course
Introduction to wave propagation and sound. General
concepts such as quantitative measures of sound, plane waves, and
acoustic energy density and intensity. Derivation of wave equation.
Sound radiation from vibrating bodies. Basic ray-acoustic concepts:
reflection, refraction, diffraction and scattering of acoustic waves.
Normal modes: vibrating membranes, sound in a rectangular enclosue
and propagation in waveguides. Other topics may include Helmholtz
resonators, acoustic horns, propagation in startified media, acoustic
arrays, and absorption and attenuation of sound waves.
Distance Learning: Available to BU and NU Students
Only
Day(s) and Time(s): Tuesday, Thursday 2:00
to 4:00pm
Lasers
(ENG SC 570)
Prof. Mal Teich - Graduate
Course
Review of wave optics. Gaussian and Hermite-Gaussian
optical beams. Planar-and spherical-mirror resonators. Photon streams.
Absorption, spontaneous emission, and simulated emission. Laser amplification
and gain saturation. Laser oscillation; pulsed lasers. Photon interactions
in semiconductors. LEDs and semiconductor injection lasers. Photon
detectors. Laboratory experiments: beams; divergence and collimation;
electroluminescence; semiconductor injection lasers. 4 cr.
Prerequisites:
CAS PY313
Distance Learning:
Available
to Boston Area Students
Day(s) and Time(s):
Tuesdays and Thursdays - 4:00pm to 6:00pm
Image
Reconstruction and Restoration (ENG SC 717)
Prof. W. Clem Karl - Graduate
Course
Principles and methods
of reconstructing images and estimating multidimensional fields from
indirect and noisy data; general deterministic (variational) and stochastic
(Bayesian) techniques of regularizing ill-posed inverse problems;
relationship of problem structure (data and models) to computational
efficiency; impact of typically large image processing problems on
viability of solution methods; problems in imaging and computational
vision including tomography and surface reconstruction. Computer assignments.
4 cr.
Prerequisites:
ENG SC 416 and SC 505
Distance Learning:
Available
to Boston Area Students
Day(s) and Time(s):
Mondays and Wednesdays - 12:00pm to
2:00pm
Optical
Measurement (ENG SC 764)
Prof. Alexander Sergienko - Graduate
Course
Detailed discussion of basic principles of major optical
effects such as interference, diffraction, and polarization. Analysis
of practical applications of interferometry, ellipsometry, photometry,
and laser spectroscopy in modern optical measurement such as characterization
of industrial processes, environmental control, communication, and
laboratory research. 4 cr.
Prerequisites: ENG SC 560
Distance Learning: Available
to BU and NU Students Only
Day(s) and Time(s): Monday, Wednesday, 2:00pm
to 4:00pm
Guided-Wave
OptoElectronics (ENG SC 770)
Prof. Selim Unlu - Graduate
Course
Discussion of physics and engineering aspects of integrated
optics and optoelectronic devices. Semiconductor waveguides, lasers,
and photodetectors. Layered semiconductor structures, quantum wells,
and superlattices. QW detectors, emitters, and modulators. OEICs.
Photonic switching. 4 cr.
Prerequisites: None
Day(s) and Time(s): Monday, Wednesday, 4:00pm
to 6:00pm
Distance Learning: Available to BU and NU Students
Only, Fall 2005 - NU, Offered by Distance Learning to ALL CenSSIS
Partners
Northeastern
University
Biological
Imaging (BIO U581 and BIO G281)
Prof. Donald O'Malley - Graduate
and Undergraduate Course
This course will introduce students to state-of-the-art
optical and imaging techniques that are used in the biological and
biomedical sciences. Advances in Optical & Imaging Techniques,
together with new Optical Probes, have fostered a revolution in Biological
Imaging. Such methodologies now influence every area of biology, especially
cell biology, developmental biology, molecular biology and neurobiology.
The 3-fold goals of this course are to:
(1) Briefly introduce students to the physics underlying
microscopic imaging,
(2) Survey the diverse array of techniques & devices
used in biological imaging, and
(3) Explore cutting edge imaging applications in the
biomedical research literature.
Course Emphasis: In the context of surveying
the latest imaging techniques, this course addresses major and fundamental
problems in several areas of cell biology and neurobiology. Much of
the course looks at the molecular-level organization and function
of eukaryotic cells, focusing upon such topics as: organelles and
intracellular trafficking, membrane structure, ion dynamics, visualization
of gene expression and synaptic/developmental processes in neurons.
Later in the course we will learn about human brain mapping and gene
chips. The range of optical techniques encountered includes: light
and fluorescence microscopy, DIC-video, laser tweezers, laser ablation,
atomic force microscopy, confocal and 2-photon imaging. The use of
these techniques to address critical research questions is examined
by reviewing prominent new findings in these fields.
Prerequisites: Biochemistry or Genetics. This
course is intended for Junior/Senior students in Biology and related
disciplines, as well as graduate students. Students with a science
background, but lacking biochemistry, should consult the instructor.
Graduate students will be graded separately from undergraduate students.
Notes: If you send me an email I will put you
on my course mailing list. Also, if you previously took Optical Methods
in Cell Biology, you should not take this class.
Distance Learning: Available to BU and NU Students
Only
Day(s) and Time(s): Monday, Wednesday, Thursday
10:30am to 11:35am
Biomedical Signal Processing and Imaging (ECE U664)
Prof. Dana Brooks - Undergraduate
Course for upperlevel (junior/senior) undergrads
The first part of this course will cover some important
bioelectric signals, with particular emphasis on electroencephelograms
and electrocardiograms, and relevant signal processing techniques
for these signals. The second part ill be a survey of some medical
imaging modalities including CT, PET and SPECT, ultrasound, and MRI,
with emphasis on image formation from a signal processing point of
view. The exact coverage will depend partly on student background
and interest, and students will be expected to participate actively
in the class.
Prerequisites: A Probability or Stochastic
Processes course and a Linear Systems course
Distance Learning: Available to BU and NU students
only.
Day(s) and Time(s): TBA
Data
Structures (ISY G205)
Prof. Jennifer Black - Graduate
Course
Presents data structures and related algorithms, beginning
with a brief review of dynamic memory allocation. The fundamental
data structures will be discussed in detail, including the abstract
representation, supporting algorithms, and implementation methods.
Focuses on understanding the application of the abstract data structure
and the circumstances that affect implementation decisions. Covers
lists, stacks, queues, trees, hash tables, and graphs. Covers recursion
and searching and sorting algorithms in detail. Emphasizes data abstraction
and encapsulation in code design. Time permitting, external storage
structures will be explored.
Prerequisite: ISYG090, or equivalent
Distance Learning: Yes
Day(s) and Time(s): Monday, Wednesday 6:00pm
to 9:30pm
Electromagnetic
Theory 2 (ECE G270)
Prof. Philip Serafim - Graduate
Course
Continues ECE G202. Examines important electrodynamic
applications by the use of advanced mathematical techniques. Topics
include general theory of wave-guides and resonators with application
to the cylindrical geometry; dielectric rod wave-guide; optical fibers;
radiation; linear antennas; loop antenna; linear arrays; ray optics;
scattering and diffraction of waves for planar, cylindrical, and spherical
geometries; and effects of random media.
Prerequisites: ECE G202
Distance Learning: Yes
Day(s) and Time(s): Monday, Wednesday 1:30pm
to 3:10pm
Computational
Methods in Electromagnetics (ECE G271)
Prof. Carey Rappaport - Graduate
Course
Presents solutions to problems in electromagnetics
using a wide variety of numerical and computational methods. Discusses
in detail the finite difference approximations of partial differential
equations and the finite difference time-domain method of simulating
electromagnetic wave propagation and scattering. Uses moment methods
to solve the integral equations related to currents and charges on
wire structures. Uses finite element and higher-order finite difference
methods to solve problems in electrostatics and wave propagation.
Discusses efficient matrix methods, relaxation methods, the conjugate
gradient technique, and multidimensional Newton's method in the context
of electromagnetic field simulation.
Prerequisite: ECE G202
Distance Learning: Yes
Day(s) and Time(s): Monday, Wednesday 3:20pm
to 5:00pm
Pattern
Recognition (ECE G313)
Prof. Jennifer Dy - Graduate
Course
Discusses introductory concepts, statistical classification
problem, and the Bayes classifier. Covers parametric estimation and
supervised learning, ML and Bayes approaches, and Bayes learning.
Topics include nonparametric techniques, Parzen windows, nearest neighbor
rules, convergence properties, and error bounds. Examines linear discriminant
functions, linear separability, perceptrons and their training, and
relaxation techniques. Discusses unsupervised learning and clustering,
unsupervised Bayes learning, ML estimates, k-means algorithm, and
learning vector quantization. Introduces neural network structures,
feed-forward nets, ADALINE, Widrow-Hopf approach, the back propagation
training algorithm, Kolmogorov's theorem, and capacity of feed-forward
nets. Focuses on Hopfield model and learning, associative memory,
bidirectional associative memory, stable states and convergence, and
capacity of the Hopfield model. Also covers unsupervised learning,
adaptive resonance theory, and self-organizing feature maps.
Prerequisites: ECE G204
Distance Learning: Available to BU and NU Students
Only
Day(s) and Time(s): Monday, Wednesday, Thursday
1:30pm to 3:10pm
Digital
Image Processing (ECE G315)
Prof. Vinaykumar Ingle - Graduate
Course
Focuses on generation of digital image from the source;
image digitizers and display devices; image transforms; enhancement
techniques, such as histogram, equalization, and edge sharpening;
restoration by Wiener and Kalman filters; image coding using run-length
coding; DPCM; transform coding; and feature analysis.
Prerequisite: ECE G110
Distance Learning: Available to BU and NU Students
Only
Day(s) and Time(s): Tuesday, Thursday 1:30pm
to 3:10pm
Rensselaer
Polytechnic Institute
Introduction
to Radar Imaging (MATH 6791)
Prof. Margaret Cheney - Graduate
Course
Radar imaging is a technology that has been developed,
very successfully, within the engineering community during the last
50 years. Radar systems on satellites now make beautiful images of
regions of our earth and of other planets such as Venus. One of the
key components
of this impressive technology is mathematics, and many of the open
problems are mathematical ones.
This course will
explain, from first principles, the basics of radar and the mathematics
involved in producing high-resolution radar images.
Day(s) and Time(s):
Monday and Thursday, 10:00am to 12:00pm
Distance Learning: NO