The students will learn about engineering and optimization of modern complex information gathering and utilization systems from the modeling of the subsystems and estimators to the abstraction of these systems in terms of information of oriented metrics and the integration and optimization of such systems. They will learn how advanced multi-objective optimization methods are used to generate design vectors in design space and their image in objective space for purposes of supporting the decision making that drives the optimization and evolution of such engineered systems.

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Introduction to fundamentals of radar systems. Radar range equation, critical radar components, and system performance. Detection, modulation, noise, and propagation effects. Prerequisite: E&C-ENG 584 or equivalent.

Theory and techniques used in the design of modern microwave and millimeter wave active circuits. Emphasis on amplifier and oscillator circuits using devices such as FETs, HEMTs, HBTs and optoelectronic devices. Modern reference material used as much as possible. Prerequisite: E&C-ENG 585.

A graduate version of E&C-Eng 568. Quantitative study of pipelined processor architectures, memory, Input/Output, RISC processors and vector machines. Prerequisite: undergraduate courses in digital design and hardware organization.

Modern techniques for synthesis and verification of digital systems. Topics in synthesis cover high-level synthesis, decision diagrams, multi-level logic and sequential optimization. Topics in verification include symbolic techniques, combinational and sequential equivalence checking, and functional test generation. Open to Graduate Students only. Recommended Prerequisites in the following: "Undergraduate courses in digital logic design and hardware organization"

Introduction to the design and analysis of algorithms. Topics include basic algorithmic paradigms (e.g. divide-and-conquer, dynamic programming, the greedy approach and randomization), their application to core problems in graph theory and optimization, as well as analysis of time and space complexity.

Introduction to digital communications at the graduate level. Signaling formats, optimal receivers, and error probability calculations. Introduction to error control coding, source coding, and information theory. Prerequisite: undergraduate probability.