|
|
- Spring 2007:
-
Real-Time and Embedded Systems
-
Professor
Amy
Larson
- Book:
Real-Time Systems by Jane
Liu.
- Topics:
Introduction to
real-time systems, scheduling techniques, programming
techniques, resource management, synchronization,
communication, and determinism. Lab work on embedded RTS.
-
Computational Vision and Robotics
-
Professor
Nikolaos Papanikolopoulos
- Book: Selected papers.
- Topics covered:
active vision, mapping, localization, motion analysis,
distributed sensing/estimation, distributed robotics, mobile
robots, sensing for humanoids, stereo, surface and solid
representation, shape recovery, edge detection, image
segmentation, texture analysis, vision-based navigation,
applications, and medical imaging.
|
|
|
- Fall 2006:
-
Advanced Topics in Estimation and Filtering
-
Professor Tryphon T. Georgiou
- Book: Optimal State Estimation:
Kalman, H_infinity, and Nonlinear Approaches by D.
Simon.
- Topics: least-squares estimation
& “linear-quadratic” estimation, Gauss-Markov model,
linear filtering, discrete-time Kalman filter,
computational aspects: square-root filters, and fast
algorithms; Levinson, Wiener, continuous-time
Kalman-Bucy filter, optimal smoothing; H∞
filtering; nonlinear filtering; extensions of Kalman
filter, particle filters, and Monte Carlo methods.
-
Data Communications and Computer Networks
-
Professor Zhi-Li Zhang
- Book: Computer Networks: A Systems
Approach, by Larry L. Peterson and Bruce S. Davie,
Morgan Kaufman.
- Introduction to computer networks,
layered network architectures, applications, network
programming interfaces, transport, data link and media
access protocols, local area networks and network
routing.
- I was the TA of
Computational Aspects of Matrix Theory
this semester.
|
|
|
- Spring 2006:
-
Convex Optimization
-
Professor Tom Lou
- Book: Convex Optimization
by Stephen Boyd and Lieven Vandenberghe
- Topics
covered: Convex sets and functions, Convex
optimization problems, KKT condition and duality,
Unconstrained minimization, Interior-point methods,
Derivative free optimization methods, Introduction
to computational complexity theory, Relaxations and
approximation algorithms, Applications (signal
processing, communication, statistics, ...)
- I was the TA of
Numerical Computing this semester.
- Fall 2005:
-
Introduction to Intelligent Robotic Systems
-
Professor Stergios Roumeliotis
- Book: Introduction to Robotics:
Mechanics and Control by John Craig
- Topics covered: Transformations,
kinematics/inverse kinematics, dynamics, control.
Sensing (robot vision, force control, tactile sensing),
applications of sensor-based robot control, robot
programming, mobile robotics, and microrobotics.
-
Computational Aspects of Matrix Theory
-
Professor Yousef Saad
- Books:
- Matrix Computations by Gene
Golub and Charles Van Loan
- Applied Numerical Linear Algebra
by James Demmel
- Topics covered: Perturbation theory
for linear systems and eigenvalue problems. Direct and
iterative solution of large linear systems.
Decomposition methods. Computation of eigenvalues and
eigenvectors. Singular value decomposition. LAPACK and
other software packages. Methods for sparse and large
structured matrices.
-
Probability and Stochastic Processes
-
Professor Jae Moon
- Book: Probability and Random
Processes with Applications to Signal Processing (3rd
Edition) by John Woods and Henry Stark
- Topics covered: Introduction to basic
concepts of probability theory, statistical techniques,
and development of probability models, Random variables,
multiple random variables, the central limit theory and
long term averages, random sequences, convergence of
random sequences, law of large numbers, random
processes, mean square calculus, stochastic integral and
differential equations, ergodicity, Karhunen-Loeve
expansions, estimation and decision theory, Wiener
filter and Kalman filter, Markov chains and introduction
to Queuing Theory.
|
- Spring 2005:
-
Estimation and Detection Theory
-
Professor Georgios Giannakis
- Books:
- Statistical Signal Processing:
volume I, Estimation Theory by Steven Kay
- Statistical Signal Processing:
volume II, Detection Theory by Steven Kay
-
Computer Vision
-
Professor Paul Schrater
- Books:
- Computer Vision, A Modern Approach
by David Forsyth and Jean Ponce
- Multiple View Geometry in Computer
Vision by Richard Hartley and Andrew Zisserman
- Topics covered: Issues in perspective
transformations, study of light, color, shadows,
shadings and sources. Camera models and calibration.
Edge detection, image filtering, image segmentation, and
feature tracking. Epipolar geometry, complex problems in
shape recovery, stereo vision, active vision, autonomous
navigation, shadows, and physics-based vision.
Applications.
-
Advanced Topics in Computer Vision
-
Professor
Nikolaos Papanikolopoulos
- Book: Selected papers.
- Topics covered: The course will
discuss issues in active vision, motion analysis,
stereo, surface and solid representation, shape
recovery, edge detection, image segmentation, texture
analysis, vision-based navigation, applications, and
medical imaging.
|
|
