Department of Computer Science and Engineering
Wright State University

CEG 428 Linear Optical Systems for Computer Engineers

Catalog Data

[4 credit hours] Introduction to linear optical systems, transformation properties of optical systems, correlation, convolution, diffraction, applications related to optical computers, such as beam steering for optical interconnection, digital multiplication by analog convolution, and parallel optical algorithm for pattern search, neural network. Prerequisites : EE 321, 322.

Text Books and Other Source Materials

  1. J. D. Gaskill, Linear Systems, Fourier Transforms and Optics, John Wiley & Sons, Inc. New York, 1978, ISBN 0-471-29288-5.
  1. J. W. Goodman, Introduction to Fourier Optics, McGraw-Hill, 1996, ISBN 0-07-024254-2.
  1. Selected papers published in refereed journals such as Applied Optics, Optical Engineering.

Schedule

Each week has two lectures of 75-minutes each. There is no scheduled lab. Students are expected to work in open labs for no less than 2 hours a week.

Prerequisites by Topic

  1. Complex algebra.
  2. Impulse response.
  3. Linear system theory and convolution
  4. Discrete Fourier transform using matlab.
  5. Fourier transform.
  6. Matlab tools.

Course Content

Wk / Topics / Read
1 / Optical functions and representation / Gaskill – Chap. 2-5
2 / Optical linear system theory: Correlation and convolution / Gaskill – Chap. 6
3 / Fourier transform and properties / Gaskill – Chap 7
4 / Linear filtering applications: complex, amplitude and phase filter / Gaskill – Chap 8
5 / 2-D Fourier transforms, simulation using digital computers (2D FFT) / Gaskill – Chap 9; Goodman – Chap 2
6 / Propagation of lasers: short distance (Fresnel) and long distance (Fraunhoffer) / Goodman – Chap 4
7-8 / Optical information processing I: Fourier transform using lenses, pattern recognition algorithm / Goodman – Chap 5,8
9-10 / Optical information processing II: optical holography, computer generated holograms / Goodman – Chap 9

Learning Objectives and Desired Outcomes

The student should have learned the following:

  1. Complex representation of optical signals.
  2. Optical linear systems theory and point spread function
  3. correlation and convolution
  4. 1-D and 2-D Fourier transform and its properties
  5. Linear Optical filtering: amplitude filter, phase filter and complex filter
  6. Simulation of optical filtering using matlab.
  7. Propagation of optical information
  8. Fourier transform using lenses
  9. Optical pattern recognition.
  10. Optical holography: recording and generation

The student should be able to apply the concepts above to the following:

  1. Manipulation of optical signals as complex quantities.
  2. 3-D representation and visualization of optical functions. Transformation of optical function. Mathematically manipulate expressions involving these functions.
  3. Harmonic decomposition of simple signals and its optical importance and/or interpretation.
  4. Optical impulse function or point spread function.
  5. Conditions for a linear shift invariant system.
  6. Complex exponentials as eigenfunctions
  7. Graphical and mathematical convolution, correlation of complex and complicated optical signals.
  8. Fourier transforms of real and complex signals and their optical representation.
  9. Important properties of optical Fourier transform and its relationship with geometrical optics.
  10. Analyze linear shift invariant system using Fourier transform technique.
  11. Linear optical filtering – effect of an amplitude, phase and complex filter.
  12. Optical techniques of extracting signal from signal plus noise.
  13. Sampling theorem and recovery of optical sampled signals.
  14. Signal detection using matched filter.
  15. Analyze propagation of light as a linear system phenomenon.
  16. Analyze light propagation under different boundary condition and different transmittance function.
  17. Analyze the coherent optical system using linear systems tools based on wave-optics.
  18. Analyze effect of a lens in an optical system, when the position of the input object is varied.
  19. Design and analysis of an optical information processing system such as phase-contrast microscopy.
  20. Design and analysis of a VanderLugt filter.
  21. Analysis of a joint Fourier transform correlator.
  22. Analysis of a phase only filter and complex matched.
  23. Implement optical correlators using matlab.
  24. Optical techniques of recording and reconstruction of holograms.
  25. Computer simulation of a holographic memory.

Outcome Measures and Assessment

Student progress in achieving the desired objectives and outcomes for this course will be monitored and measured through use of entrance and exit surveys, programming assignments, homework, quizzes, examinations, and success in the courses that use CEG 320 as a prerequisite.


Department of Computer Science and Engineering
Wright State University

CEG 428 Linear Optical Systems for Computer Engineers

Assessment of Prerequisites
Entrance Survey
Fall 1998, Section 01. Your Name (optional): ______

The following survey is being conducted at the entrance, during the first week of classes. Results from the collected data are used to improve how our courses are conducted. Please complete as well as you can. Please feel free to attach in a separate sheet any comments that you may have.

This course depends on material taught in the prerequisite courses listed. We would like to learn if you have the background that we expect for this course as shown in the prerequisites listed by topic in Table 2. Please give us the instructor's name so that we may give him/her this feedback.

Table 1: Prerequisites by Courses

Course Number / Taken at / Term/Year / Instructor's Name / Grade
EE 322

Please assess how well you were prepared by assigning to yourself a letter grade (A, B, C, D, or F) to each of the prerequisite topics listed.

Table 2: Prerequisites by Topic

Prerequisite Topic / Grade
Complex algebra.
Impulse response.
Linear System theory and convolution
Discrete Fourier transform using matlab.
Fourier transform.
Matlab tools.


Department of Computer Science and Engineering
Wright State University

CEG 428 Linear Optical Systems for Computer Engineers

Assessment of Learning Objectives and Desired Outcomes
Exit Survey

Fall 1998, Section 01. Your Name (optional): ______


The following survey is being conducted during the final week of classes. Results from the collected data are used to improve our courses.

Please feel free to attach a separate sheet of comments.

This course has the learning objectives listed below. In your opinion, how well did the course accomplish its objectives? Please fill in a letter grade (A, B, C, D, or F).

Table 1: Learning Objectives

Complex representation and manipulation of optical signals.
Optical linear systems theory and point spread function
correlation and convolution
1-D and 2-D Fourier transform and its properties
Linear Optical filtering: amplitude filter, phase filter and complex filter
Propagation of optical information
Fourier transform using lenses
Optical pattern recognition using lenses.
Optical holography: recording and generation

This course has the following desired outcomes. In your opinion, how well did the course accomplish these? Please fill in a letter grade (A, B, C, D, or F).


Table 2: Desired Outcomes

Manipulation of optical signals as complex quantities.
3-D representation and visualization of optical functions. Geometric and algebraic transformations of optical function.
Harmonic decomposition of simple signals and its optical importance and/or interpretation.
Know what is an optical of impulse function.
Conditions for a linear shift invariant system.
Complex exponentials as eigenfunctions
Graphical and mathematical convolution, correlation of complex and complicated optical signals.
Fourier transforms of real and complex signals and their optical representation.
Important properties of optical Fourier transform and its relationship with geometrical optics.
Analyze linear shift invariant system using Fourier transform technique.
Linear optical filtering – effect of an amplitude, phase and complex filter.
Optical techniques of extracting signal from signal plus noise.
Sampling theorem and recovery of optical sampled signals.
Signal detection using matched filter.
Analyze propagation of light as a linear system phenomenon.
Analyze light propagation under different boundary condition and different transmittance function.
Analyze the coherent optical system using linear systems tools based on wave-optics.
Analyze effect of a lens in an optical system, when the position of the input object is modified.
Design and Analysis an optical information processing system such as phase-contrast microscopy.
Design and analysis of a VanderLugt filter.
Analysis of a joint Fourier transform correlator.
Analysis of a phase only filter and complex matched.
Implement optical correlators using matlab / 1. 
Optical techniques of recording and reconstruction of holograms.
Computer simulation of a holographic memory.


Department of Computer Science and Engineering
Wright State University

CEG 428 Linear Optical Systems for Computer Engineers

Program Outcomes and Assessment of a Single Course

Table of Criteria 3: Students who have successfully completed the course have

a1 / an ability to apply knowledge of mathematics / PXX
a2 / an ability to apply knowledge of science / PX
a3 / an ability to apply knowledge of engineering / PXX
b1 / an ability to design and conduct experiments / X
b2 / an ability to analyze and interpret data / X
c / an ability to design a system, component, or process to meet desired needs / PXX
d / an ability to function on multi-disciplinary teams / PXX
e / an ability to identify, formulate, and solve engineering problems / PXX
f / an understanding of professional and ethical responsibility / 0
g / an ability to communicate effectively / 0
h / the broad education necessary to understand the impact of engineering solutions in a global and societal context / X
i / a recognition of the need for, and an ability to engage in life-long learning / X
j / a knowledge of contemporary issues / X
k / an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice / PXX
Supporting Statements

a1- a3: This course on linear optical systems is a multidisciplinary course which incorporates topics from mathematics, engineering system theory as well as optics.

a1: This course builds on mathematical foundation acquired previously in both mathematics and linear systems courses. Background in Fourier transform, differential equations, partial differential equations, and integration are heavily used. Students must have good background in integral calculus and complex mathematics.

a2: The physical foundation of this course is optics i.e. physical sciences. Many physical phenomena are seen from an engineering perspective. For example, a Fraunhoffer pattern is seen as a Fourier transform of the input. Thus it analyzes sees optics in a totally new light and makes available to the students engineering tools that can be used to analyze as well as design an optical system. Many of the basic formulae used in this course have their origin in electromagnetics. Strong background oh physics is useful but not required.

a3: The linear optical systems for computer engineers course uses the linear systems course (EE 321 and EE 322) as prerequisite. Engineering analysis tools learned in these courses are applied here to analyze and design optical system for specific purposes such as designing an optical correlator, a system for filtering noise in an optical image etc. Moreover, this course helps to create additional insight into the linear system theory which is not possible in any other course. The reason for this is that everything learned in a linear system course could be visualized here optically. Concepts of say linear systems, Fourier transform etc. are seen as an optical image. It also allows the students to visualize mathematics.

b1: Problems worked out in this course are very much related to optical signals and set up where certain parameters are modified and the corresponding results evaluated. In this process, students are trained to develop an experimental edge.

b2: Since they do parameter modification as stated in the previous bullet, they also have to analyze in an intuitive sense, what is the effect of change of this parameter on the overall system.

c: The Matlab used in this course in additional to analytical development, allows one to design an experiment completely in the computer. Thus the students are able to design systems of a say pattern recognition system or a holographic memory etc.

d: Since this course is heavily multidisciplinary in nature, it may be argued that students completing this course will be able to see a physical phenomena with at least three different eyes: those of a mathematician, a physicist, an engineer, and a computer programmer. Appreciation of the other point of view will help them work effectively in a multidisciplinary team.

e: This course aims at providing engineering tools to solve physical problems which has optical solutions. Part of the course emphasizes how to formulate a problem so that it is solvable using engineering tools.

h: Optical problems presented in this course are very much related to real-world engineering problems. Some of these are in the cutting edge of the technology. Phase contrast microscopy, holographic memory, optical pattern recognition techniques are being researched for real-world applications such as in medicine, computer industry and machine vision or manufacturing environment.

i-j: Optics is a major field that is expected to have an enormous impact in the twenty first century. Students are exposed to most recent relevant material by providing them copies of recently published articles, and home work assignments based on these. Thus the students feel closeness with the rapidly expanding field of optical information processing, while at the same time be aware of the contemporary issues of optics in general.

k: Students uses computer tools such as matlab to perform their homeworks. In addition, the most important mathematical tools that they learn to use here are linear systems tools. Formulate a problem as linear systems, and then solve it using these known tools used frequently in a linear systems course. Both of these tools are used in many other courses such as machine vision, digital image processing and they have tremendous applications in the industry.