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3.16
Spring 2025
Design and analysis of passive microwave circuits. Topics include transmission lines, electromagnetic field theory, waveguides, microwave network analysis and signal flow graphs, impedance matching and tuning, resonators, power dividers and directional couplers, and microwave filters. Prerequisite: ECE 3209 or instructor permission.
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3.74
Spring 2025
A first-level graduate/advanced undergraduate course covering a topic not normally covered in the course offerings. The topic usually reflects new developments in the electrical and computer engineering field. Offering is based on student and faculty interests. Prerequisite: Instructor permission.
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Fall 2025
This course will teach students the required skills, concepts, and algorithms to develop mobile robots that act autonomously in complex environments. The main emphasis is on mobile robot locomotion and kinematics, control, sensing, localization, mapping, path planning, and motion planning. Besides theory, students are exposed to simulation environments and lab exercises with real robotic systems.
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3.55
Fall 2024
Introduces semiconductor device operation based on energy bands and carrier statistics. Describes operation of p-n junctions and metal-semiconductor junctions. Extends this knowledge to descriptions of bipolar and field effect transistors, and other microelectronic devices. Related courses: ECE 5150, 6155, and 6167. Prerequisite: ECE 3103 or equivalent, or solid state materials/physics course.
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Spring 2025
Explores measurement and behavior of high-frequency circuits and components. Equivalent circuit models for lumped elements. Measurement of standing waves, power, and frequency. Use of vector network analyzers and spectrum analyzers. Computer-aided design, fabrication, and characterization of microstrip circuits. Corequisite: ECE 5260 or instructor permission.
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Fall 2025
This course explores the intricacies of AI hardware, including the current landscape and anticipating the necessary developments in response to AI's rapid growth and widespread integration across all computing tiers. Through this exploration, you will gain an understanding of both the existing technologies and the future challenges in AI hardware design and implementation.
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Fall 2024
Focuses on techniques for designing and analyzing dependable computer-based systems. Topics include basic dependability concepts and attributes, fault models and effects, combinatorial and state-space modeling, hardware redundancy, error detecting and correcting codes, time redundancy, software fault tolerance, checkpointing and recovery, reliable networked systems, error detection techniques, and experimental dependability evaluation techniques.Prerequisites: A basic knowledge of probability and computer architecture is required. A working knowledge of programming is required for homework and mini projects.
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3.54
Spring 2025
Integration of computer organization concepts such as data flow, instruction interpretation, memory systems, interfacing, and microprogramming with practical and systematic digital design methods such as behavioral versus structural descriptions, divide-and-conquer, hierarchical conceptual levels, trade-offs, iteration, and postponement of detail. Design exercises are accomplished using a hardware description language and simulation. Prerequisite by topic: Digital Logic Design (ECE 2330 or equivalent), Introductory Computer Architecture (ECE 3330 or equivalent), Assembly Language Programming.
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3.91
Spring 2025
Interactions between robots and humans are influenced by form, function and expectations. Quantitative techniques evaluate performance of specific tasks and functions. Qualitative techniques are used to evaluate the interaction and to understand expectations and perceptions of the human side of the interaction. Students use humanoid robots to develop and evaluate interactions within a specific application context.
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3.72
Fall 2025
A first-level graduate course covering a topic not normally covered in the graduate course offerings. The topic will usually reflect new developments in the electrical and computer engineering field. Offering is based on student and faculty interests. Prerequisite: Instructor permission.
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