This course provides an overview of the core design principles used in the holistic design of low power embedded computing systems. Modern embedded system design use co-design of both hardware and software subsystems to achieve energy efficiency. The content of this class builds on foundational ECE courses in circuits, low level software design, machine learning, and signal processing. Prior courses in in at least one of these areas is recommended as a prerequisite.

Embedded systems sense, actuate, compute, and communicate to accomplish tasks in domains such as medical, automotive, and industrial controls. Informal methods of hacking together embedded systems are at odds with the criticality of their applications. This course will introduce recent developments toward more rigorous modeling and verification of embedded and cyber-physical systems.

Unified treatment of techniques for representation of signals and signal processing operations. Emphasis on physical interpre-tation of vector spaces, linear operators, transform theory, and digital signal processing with wavelet filter banks. Prerequisite: graduate standing.

Matrix analysis, state variables, state space techniques for continuous time systems, matrix fraction descriptions. Controllability, observability, realization theory. Feedback and observers. Stability analysis.

Machine learning is the practice of programming computers to learn and improve prediction through experience and data, and it is becoming pervasive in technology and science. This course will cover the mathematical underpinnings, algorithms, and practices that enable a computer to learn. Topics will include supervised learning, unsupervised learning, evaluation methodologies, and deep learning. The prerequisites of this course include introductory courses in linear algebra (e.g ECE 201 or Math 235), multivariate calculus (e.g., Math 233), and probability (e.g., ECE 214).

Not available at this time

Analysis and design of passive microwave devices, including resonators, filters, and ferrite devices, in various transmission-line media. Noise and noise effects in detectors, mixers, and modulators. Introduction to FET amplifier design. Prerequisite: E&C-ENG 584.

With lab. Semiconductor instructional processing laboratory (SIPL) and lectures. Principles and practice of modern microelectronic silicon device processing. Theory and practice of basic processing technology including photo-lithography, oxidation, diffusion, thin film deposition, ion implantation, packaging, yield, and process integration. State-of-the-art laboratory fabrication of working microelectronic devices and process simulation techniques. Prerequisite: E&C-ENG 344.

This course provides an introduction to software systems with emphasis on operating system design and implementation. A key aspect is computer architecture and system software interaction. Topics include: process management, threading, synchronization, deadlocks, scheduling, security, IO systems, and distributed systems.

Waveform coding, source coding and data compression. Pulse modulation systems: signal spaces, optimal receivers, probability of error. Baseband and bandpass data transmission. Introduction to channel coding.