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1 - 9 of 9 results for: EE102A

CS 349T: Project Lab: Video and Audio Technology for Live Theater in the Age of COVID (EE 192T)

This class is part of a multi-disciplinary collaboration between researchers in the CS, EE, and TAPS departments to design and develop a system to host a live theatrical production that will take place over the Internet in the winter quarter. The performing arts have been greatly affected by a transition to theater over Zoom and its competitors, none of which are great at delivering low-latency audio to actors, or high-quality audio and video to the audience, or feedback from the audience back to actors. These are big technical challenges. During the fall, we'll build a system that improves on current systems in certain areas: audio quality and latency over spotty Internet connections, video quality and realistic composited scenes with multiple actors, audience feedback, and perhaps digital puppetry. Students will learn to be part of a deadline-driven software development effort working to meet the needs of a theater director and creative specialists -- while communicating the effect of resource limits and constraints to a nontechnical audience. This is an experimental hands-on laboratory class, and our direction may shift as the creative needs of the theatrical production evolve. Based on the success of class projects and subsequent needs, some students may be invited to continue in the winter term with a research appointment (for pay or credit) to operate the system you have built and instruct actors and creative professionals how to work with the system through rehearsals and the final performance before spring break. Prerequisites: CS110 or EE102A. Recommended: familiarity with Linux, C++, and Git.
Last offered: Autumn 2020

EE 101B: Circuits II

Continuation of EE101A. Introduction to circuit design for modern electronic systems. Modeling and analysis of analog gain stages, frequency response, feedback. Filtering and analog to digital conversion. Fundamentals of circuit simulation. Prerequisites: EE101A, EE102A. Recommended: MATH 53 or CME102.
Terms: Spr | Units: 4 | UG Reqs: WAY-SMA, GER:DB-EngrAppSci

EE 102A: Signals and Systems I

Concepts and tools for continuous- and discrete-time signal and system analysis with applications in signal processing, communications, and control. Mathematical representation of signals and systems. Linearity and time invariance. System impulse and step responses. System frequency response. Frequency-domain representations: Fourier series and Fourier transforms. Filtering and signal distortion. Time/frequency sampling and interpolation. Continuous-discrete-time signal conversion and quantization. Discrete-time signal processing. Prerequisites: MATH 53 or CME 102. EE 102A may be taken concurrently with either course, provided students have proficiency in complex numbers.
Terms: Win | Units: 4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR

EE 155: Green Electronics (EE 255)

Many green technologies including hybrid cars, photovoltaic energy systems, efficient power supplies, and energy-conserving control systems have at their heart intelligent, high-power electronics. This course examines this technology and uses green-tech examples to teach the engineering principles of modeling, optimization, analysis, simulation, and design. Topics include power converter topologies, periodic steady-state analysis, control, motors and drives, photovol-taic systems, and design of magnetic components. The course involves a hands-on laboratory and a substantial final project. Formerly EE 152. Required: EE101B, EE102A, EE108. Recommended: ENGR40 or EE122A.
Last offered: Autumn 2018

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 2022

EE 192T: Project Lab: Video and Audio Technology for Live Theater in the Age of COVID (CS 349T)

This class is part of a multi-disciplinary collaboration between researchers in the CS, EE, and TAPS departments to design and develop a system to host a live theatrical production that will take place over the Internet in the winter quarter. The performing arts have been greatly affected by a transition to theater over Zoom and its competitors, none of which are great at delivering low-latency audio to actors, or high-quality audio and video to the audience, or feedback from the audience back to actors. These are big technical challenges. During the fall, we'll build a system that improves on current systems in certain areas: audio quality and latency over spotty Internet connections, video quality and realistic composited scenes with multiple actors, audience feedback, and perhaps digital puppetry. Students will learn to be part of a deadline-driven software development effort working to meet the needs of a theater director and creative specialists -- while communicating the effect of resource limits and constraints to a nontechnical audience. This is an experimental hands-on laboratory class, and our direction may shift as the creative needs of the theatrical production evolve. Based on the success of class projects and subsequent needs, some students may be invited to continue in the winter term with a research appointment (for pay or credit) to operate the system you have built and instruct actors and creative professionals how to work with the system through rehearsals and the final performance before spring break. Prerequisites: CS110 or EE102A. Recommended: familiarity with Linux, C++, and Git.
Last offered: Autumn 2020

EE 255: Green Electronics (EE 155)

Many green technologies including hybrid cars, photovoltaic energy systems, efficient power supplies, and energy-conserving control systems have at their heart intelligent, high-power electronics. This course examines this technology and uses green-tech examples to teach the engineering principles of modeling, optimization, analysis, simulation, and design. Topics include power converter topologies, periodic steady-state analysis, control, motors and drives, photovol-taic systems, and design of magnetic components. The course involves a hands-on laboratory and a substantial final project. Formerly EE 152. Required: EE101B, EE102A, EE108. Recommended: ENGR40 or EE122A.
Last offered: Autumn 2018

EE 274: Data Compression: Theory and Applications

The course focuses on the theory and algorithms underlying modern data compression. The first part of the course introduces techniques for entropy coding and for lossless compression. The second part covers lossy compression including techniques for multimedia compression. The last part of the course will cover advanced theoretical topics and applications, such as neural network based compression, distributed compression, and computation over compressed data. Prerequisites: basic probability and programming background ( EE178, CS106B or equivalent), a course in signals and systems ( EE102A), or instructor's permission.
Terms: Aut | Units: 3

EE 292S: Understanding the Sensors in your Smartphone

This course provides an introduction to the sensor systems found in modern-day smartphones, wearables, and hearable devices. As much as we take their functionality for granted, there is a tremendous amount of engineering needed to sense "real world" signals such as acceleration, touch, or altitude. There will be an overview on the actual circuitry and hardware used in sensor implementations, with a focus on MEMS devices (eg, accelerometer/gyro), going up through the algorithms commonly seen in sensors processing, and finally fusion of data from multiple sensors to yield final data presented to a user. The four broad areas that will be covered are: Inertial sensing/movement; Touch sensing/authentication; Health sensing (PPG, ECG, SpO2); Next-generation (force, radar/ranging, ultrasonics, and more). There is a lab/project associated with each of these areas, each project spanning roughly two weeks. The projects are designed to be more at a system level; the student will be required to ex more »
This course provides an introduction to the sensor systems found in modern-day smartphones, wearables, and hearable devices. As much as we take their functionality for granted, there is a tremendous amount of engineering needed to sense "real world" signals such as acceleration, touch, or altitude. There will be an overview on the actual circuitry and hardware used in sensor implementations, with a focus on MEMS devices (eg, accelerometer/gyro), going up through the algorithms commonly seen in sensors processing, and finally fusion of data from multiple sensors to yield final data presented to a user. The four broad areas that will be covered are: Inertial sensing/movement; Touch sensing/authentication; Health sensing (PPG, ECG, SpO2); Next-generation (force, radar/ranging, ultrasonics, and more). There is a lab/project associated with each of these areas, each project spanning roughly two weeks. The projects are designed to be more at a system level; the student will be required to explore the performance and limitations of sensing hardware, and then take that understanding to solve real-world sensor problems. All projects will be built on a Raspberry Pi with various sensor boards; students should be comfortable with wiring up a small breadboard, and coding on an RPi a high-level language such as Python or Java. Prerequisites: EE101A, EE102A, and CS106A or equivalents.
Terms: Aut | Units: 3
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