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Course Criteria
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3.00 Credits
Staff Topic to be announced in the Schedule of Classes. (Fall and spring)
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3.00 Credits
Staff Applied research and experimentation projects, as arranged. Prerequisite: junior or senior status. (Fall and spring)
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4.00 Credits
Korman and Staff Lecture (3 hours), laboratory (3 hours). Solid-state devices used in electronic engineering. Physics of their operation. Application to electronic circuits. Primary emphasis on application of these elements in power supplies and in linear amplifiers. Design concepts through use of SPICE and graphical techniques. Prerequisite: ECE 11. (Fall and spring)
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3.00 Credits
Lang and Staff Maxwell's equations, pulse propagation in one dimension, transmission line equations, reflection coefficient, capacitance and inductance calculations, Smith chart, plane waves, reflection from a dielectric of fiber and integrated optics. Prerequisite: ApSc 113, Phys 22. (Spring)
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3.00 Credits
Kahn and Staff Complex phasor notation, uniform transmission lines, standing wave ratio, power, reflection coefficient, impedance matching. Review of vector analysis and numerical methods. Electrostatics, generalizations of Coulomb's law, Gauss's law, potential, conductors, dielectrics, capacitance, energy. Prerequisite: ApSc 113; Phys 22. (Spring)
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3.00 Credits
Kahn and Staff Magneto-stationary fields, Lorentz force torques, Biot-Savart law, Ampere's law, magnetic materials, inductance, energy. Maxwell's equations, Faraday's law, charge-current continuity, vector potential. Time-harmonic fields, plane waves, polarization, skin effect, dielectric boundaries, and fiber optics. Radiation, dipole, gain, effective area. Prerequisite: ApSc 114, ECE 31. (Fa
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1.00 Credits
Mazzuchi, Soland A survey of several aspects of systems analysis, including methodologies such as linear programming, network models, probability, and queuing theory, with applications to resource allocation, decision making, and statistical analysis. Spreadsheet and laboratory exercises and projects. (Fall)
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3.00 Credits
Abeledo, Campos-Nanez and Staff Quantitative modeling techniques and their application to decision making in systems engineering. Linear, integer, and nonlinear optimization models. Stochastic models: inventory control, queuing systems, and regression analysis. Elements of Monte Carlo and discrete event system simulation. Prerequisite: ApSc 115. (Fall)
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3.00 Credits
Abeledo, Campos-Nanez and Staff Deterministic and stochastic methods. Optimization algorithms: Simplex method, Branch and Bound, combinatorial algorithms, heuristic methods. Optimization theory: convexity, duality, sensitivity analysis. Stochastic optimization: marginal analysis, Markov chains, Markov decision processes. Prerequisite: ApSc 115 and EMSE 109, or permission of instructor. (Spring)
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3.00 Credits
Abeledo and Staff Mathematical foundations of optimization theory; linear algebra, advanced calculus, convexity theory. Geometrical interpretations and use of software. Prerequisite: Math 33. (Spring)
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