University of Colorado at Boulder
Course Announcement
OPTICAL COMPUTING -ECEN 6006
Professor Kelvin Wagner
| Place: | |
| Time: | T,Th 12:30-1:45, Spring 2001 |
| Credits: | 3 |
| Text: | Readings from the literature. Most of the readings can be found in |
| the reprint collection SPIE vol 1142, by J. Caulfield and G. Gheen. | |
| Prerequisites: | Fourier Optics would be extremely useful for the first 1/4 of the course, |
| and a good optics background such as that provided by Physical Optics, Optical | |
| Electronics, or Optical Systems Design. In addition a knowledge of some | |
| of the basic principles of logic, computing, signal processing, or neural networks | |
| would be helpful. |
Course Content
This course will review the techniques and applications of optical computing
from both systems and device perspectives.
The course is intended for graduate students undertaking research in optics,
optical computing, or optical devices,
in order to provide a broad foundation and perspective
of historical and contemporary optical information processing research.
This will be a systems oriented course
where students will participate in applications oriented design projects
of optical computing systems, using available devices and required performance
specifications.
In addition, the limitations of state-of-the-art optical devices
and the ramifications of these limitations on the performance of
optical computing systems will be emphasized throughout the course.
Topics to be covered include:
Optical image processing and pattern recognition
Holography, correlators, SAR, wedge-ring detectors
Spatial light modulators, CCD detector arrays
Optical signal processing
Acoustooptic devices and systems, Matrix-vector multipliers
Optical Interconnections and Photonic Switching
Optical switches and routing networks, optical crossbars
Time, Space, Wavelength based systems, device technology
Optical data storage
Digital optical computing
Nonlinear optical logic gates, smart pixels, parallel architectures, optical arithmetic
Sequential machines, Cellular automata, Reversible computing
Optical neural networks
Photorefractive crystals and dynamic holography
Associative memory, Learning algorithms