|
|
Course Criteria
Add courses to your favorites to save, share, and find your best transfer school.
-
4.00 Credits
Lecture, 3 hours; laboratory, 3 hours. Prerequisite(s): EE 001A and EE 01LA. Sinusoidal steady state analysis, polyphase circuits, magnetically coupled networks, frequency characteristics, Laplace and Fourier transforms, Laplace and Fourier analysis. Application of SPICE to complicated circuit analysis.
-
4.00 Credits
Lecture, 3 hours; laboratory, 3 hours. Prerequisite(s): PHYS 040C (may be taken concurrently). Intended for non- Electrical Engineering majors for whom knowing the design of electrical and electronic circuits is not crucial but is helpful. Involves direct-circuit calculations with resistors, inductors, and capacitors, followed by steady state sinusoidal analysis. Discusses logic circuits before electronics, which includes diodes, amplifiers, and transistors.
-
2.00 Credits
Laboratory, 3 hours; lecture, 1 hour. Prerequisite(s): none. Introduces common everyday electrical engineering and technology devices. Aims to enrich students' appreciation of technology and the application of simple science and engineering concepts in the design and operation of these electrical and electronic devices, and to provide students with an early positive engineering experience and interaction with departmental faculty. Graded Satisfactory (S) or No Credit (NC).
-
1.00 Credits
Laboratory, 3 hours. Prerequisite(s): EE 001A (may be taken concurrently). Laboratory experiments closely tied to the lecture material of EE 001A: resistive circuits, attenuation and amplification, network theorems and superposition, operational amplifiers, transient response, application of SPICE to circuit analysis.
-
4.00 Credits
Lecture, 3 hours; laboratory, 3 hours. Prerequisite(s): EE 001B. Electronic systems, linear circuits, operational amplifiers, diodes, nonlinear circuit applications, junction and metaloxide- semiconductor field-effect transistors, bipolar junction transistors, MOS and bipolar digital circuits. Laboratory experiments are performed in the subject areas and SPICE simulation is used.
-
4.00 Credits
Lecture, 3 hours; laboratory, 3 hours. Prerequisite(s): EE 100A. Differential and multistage amplifiers, output stages and power amplifiers, frequency response, feedback, analog integrated circuits, filters, tuned amplifiers, and oscillators. Laboratory experiments are performed in the subject areas and SPICE simulation is used.
-
4.00 Credits
Lecture, 3 hours; laboratory, 3 hours. Prerequisite(s): CS 010, EE 001A, MATH 046. Introduction to the mathematical modeling of dynamical systems and their methods of solution. Advanced techniques and concepts for analytical modeling and study of various electrical, electronic, and electromechanical systems based upon physical laws. Emphasis on the formulation of problems via differential equations. Numerical methods for integration and matrix analysis problems. Case studies. Digital computer simulation.
-
4.00 Credits
Lecture, 3 hours; laboratory, 3 hours. Prerequisite(s): CS 010; EE 001B (may be taken concurrently); MATH 046. Basic signals and types of systems, linear time-invariant (LTI) systems, Fourier analysis, frequency response, and Laplace transforms for LTI systems. Laboratory experiments with signals, transforms, harmonic generation, linear digital filtering, and sampling/aliasing.
-
4.00 Credits
Lecture, 3 hours; laboratory, 3 hours. Prerequisite(s): EE 110A. Fourier analysis for discrete-time signals and systems, filtering, modulation, sampling and interpolation, z-transforms. Laboratory experiments with signals, transforms, harmonic generation, linear digital filtering, and sampling/aliasing.
-
4.00 Credits
Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): EE 110A. Covers fundamentals of probability theory, random variables, and random processes with applications to electrical and computer engineering. Includes probability theory, random variables, densities, functions of random variables, expectations and moments, and multivariate distributions. Also addresses random processes, autocorrelation function, spectral analysis of random signals, and linear systems with random inputs.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|