printer friendly pageEE 102B: Signal Processing and Linear Systems II
Continuation of
EE 102A. Concepts and tools for continuous- and discrete-time signal and system analysis with applications in communications, signal processing and control. Analog and digital modulation and demodulation. Sampling, reconstruction, decimation and interpolation. Finite impulse response filter design. Discrete Fourier transforms, applications in convolution and spectral analysis. Laplace transforms, applications in circuits and feedback control. Z transforms, applications in infinite impulse response filter design. Prerequisite:
EE 102A.
Terms: Spr
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR
Instructors:
Goldsmith, A. (PI)
EE 169: Introduction to Bioimaging
Bioimaging is important for both clinical medicine, and medical research. This course will provide a introduction to several of the major imaging modalities, using a signal processing perspective. The course will start with an introduction to multi-dimensional Fourier transforms, and image quality metrics. It will then study projection imaging systems (projection X-Ray), backprojection based systems (CT, PET, and SPECT), systems that use beam forming (ultrasound), and systems that use Fourier encoding (MRI). Prerequisites:
EE102A,
EE102B
Last offered: Autumn 2017
EE 379: Digital Communication
Modulation: linear, differential and orthogonal methods; signal spaces; power spectra; bandwidth requirements. Detection: maximum likelihood and maximum a posteriori probability principles; sufficient statistics; correlation and matched-filter receivers; coherent, differentially coherent and noncoherent methods; error probabilities; comparison of modulation and detection methods. Intersymbol interference: single-carrier channel model; Nyquist requirement; whitened matched filter; maximum likelihood sequence detection; Viterbi algorithm; linear equalization; decision-feedback equalization. Multi-carrier modulation: orthogonal frequency-division multiplexing; capacity of parallel Gaussian channels; comparison of single- and multi-carrier techniques. Prerequisite: EE102B and
EE278 (or equivalents). EE279 is helpful but not required.
Last offered: Spring 2019
RAD 206: Mixed-Reality in Medicine
Mixed reality uses transparent displays to place virtual objects in the user's field of vision such that they can be aligned to and interact with actual objects. This has tremendous potential for medical applications. The course aims to teach the basics of mixed-reality device technology, and to directly connect engineering students to physicians for real-world applications. Student teams would compete guided assignments on developing new mixed-reality technology and a final project applying mixed-reality to solve real medical challenges. Prerequisites: (1) Programming competency in a language such as C, C++. or Python. (2) A basic signal processing course such as
EE102B (Digital Signal Processing). A medical imaging course, while not required, will be helpful. Please contact the instructors with any questions about prerequisites.
Terms: Aut
| Units: 3
Instructors:
Daniel, B. (PI)
;
Leuze, C. (PI)
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