Nonswitching aspects of analog integrated circuits using bipolar or CMOS technologies. Biasing, DC signal behavior, small behavior. Emphasis on use of physical reasoning, identification of circuit functions, and use of suitable approximations to facilitate understanding and analysis. Graduate-level requirement includes greater project scope.

Enrollment Requirements

Modeling, analysis and design of digital control systems. A/D and D/A conversions. Z-transforms. Time and frequency domain representations. Stability. Microprocessor-based designs.

May be convened with ECE 442.

Enrollment Requirements

Course Texts

• Feedback Systems: An Introduction for Scientist and Engineers, Astrom and Murray.
• Feedback and Control Systems: Continuous (Analog) and Discrete (Digital), 2nd Edition. J.J. DiStefano III, A.R. Stubberud, and I.J. Williams, Schaum’s Outline Series, McGraw-Hill, 1990.

Schedule

Assessment

• Homework: 10 problem sets during semester
• Exams: 3 in-class examinations, 1 final exam
• Graduate-level requirements include additional homework and a term project

Linear control system representation in time and frequency domains, feedback control system characteristics, performance analysis and stability, design of control.

Enrollment Requirements

Course Texts

Modern Control Systems, Twelfth Edition, R.C. Dorf and R.H. Bishop, Prentice Hall, Upper Saddle River, NJ, 2011.

Schedule

Radar fundamentals: radar range equation, waveforms, ambiguity functions. Signal Processing: Pulse compression, synthetic aperture radar (SAR), inverse SAR, moving target indication (MTI), pulse-Doppler radar, space time adaptive processing (STAP).

Enrollment Requirements

This is an advanced graduate course covering the principles of digital transmission of information. We rigorously define the amount of information and introduce information measures.

The largest portion of the course is devoted to studying how to translate information into a digital signal to be transmitted, and how to retrieve the information from the received signal. We study in-depth various digital modulation schemes through a concept of signal space. We build analytical and simulation models for digital modulation systems in presence of noise, and define the performances of digital communication systems through a probability of reliable transmission of information. We also build optimal receiver models for digital base-band and band-pass modulation schemes, and introduce iterative decoding on graphs, iterative decoding on intersymbol interference channels and constrained coding.

Enrollment Requirements

Course Texts

J. G. Proakis, Digital Communications, 5th Edition, McGraw-Hill, 2012.

Schedule

Assessment

• Homework: assigned but not graded
• Project: 1-2 projects
• Exams: 2 midterm exams, 1 final exam
• Typical grading policy: 30% midterms, 20% final exam, 0% homework, 0% laboratory, 50% project

The purpose of the course is to give students a comprehensive introduction to digital communication principles. The major part of the course is devoted to studying how to translate information into a digital signal to be transmitted, and how to retrieve the information back from the received signal in the presence of noise and intersymbol interference (ISI).

Various digital modulation schemes are discussed through the concept of signal space. Analytical and simulation models for digital modulation systems are designed and implemented in the presence of noise and ISI. Optimal receiver models for digital base-band and band-pass modulation schemes are covered in detail.

Graduate work will include more challenging problem sets and exam problems, and a C/C++ simulation project.

Enrollment Requirements

Course Texts

S. Haykin, Digital Communication Systems. Wiley, 1st edition, 2014.

Schedule

Assessment

• Homework: ~10 problem sets
• Exams: 2 in-class exam, 1 mandatory final exam
• Computer usage: C/C++ exercises
• Contribution to professional component:
  • Math and basic science: 0.5 units
  • Engineering topics: 2 units
  • Significant design experience: 0.5 units

This course is designed to provide students with theoretical knowledge and practical experience to analyze and design digital image processing systems. The first part of this course covers two-dimensional signals and systems. Extension of key digital signal processing concepts (such as sampling, z-transforms, discrete Fourier transforms, and filtering) to two-dimensions are studied. During the second part of the course, properties of the human visual system are summarized and image enhancement, restoration, and compression methods are discussed. Course requirements include a project. Project ideas are developed in consultation with the instructor.

Enrollment Requirements

Course Texts

• R. C. Gonzales and R. E. Woods, Digital Image Processing, 4th Ed., Pearson, 2018. (optional)
• John Woods, Multidimensional Signal, Image, and Video Processing and Coding, 2nd Ed., Elsevier, 2012. (optional)

Schedule

Assessment

• Homework: 6-8 assignments
• Project: 1 project
• Exams: 1 midterm exam, 1 final exam
• Typical grading policy: 20% midterm, 20% final exam, 30% homework, 30% project

Discrete-time signals and systems, z-transforms, discrete Fourier transform, fast Fourier transform, digital filter design.

Enrollment Requirements

Course Texts

Oppenheim, Alan V., and Ronald W. Schafer. Discrete-Time Signal Processing. 3rd ed. Prentice Hall, 2010.

Schedule