Teaching

BEE 233: Circuit Theory

BEE 233 is intended to introduce the analysis of circuits with sinusoidal signals, phasors, system functions, complex frequency, frequency response, and computer analysis of electrical circuits, power and energy, and laboratory in basic electrical engineering topics.

Learning Objectives:

At the end of this course, a student will be able to:

1. Analyze a circuit given sinusoidal inputs in the frequency domain.
2. Compute average power consumed or supplied by a circuit.
3. Design simple circuits for maximum power transfer to a load.
4. Apply Laplace transform techniques to simplify the analysis of complex circuits.
5. Use SPICE as a computer tool to verify a design, and to confirm time-domain and frequency-domain analysis results.
6. Use basic laboratory instruments: oscilloscope, power supply, function generator, multimeter.
7. Measure basic signal parameters: amplitude, frequency, etc.

Pre-requisites: BEE 215

BEE 510: Probability and Random Processes

BEE 510 provides a rigorous introduction of probability and random processes to graduate students in electrical engineering. The course has a special emphasis on applications for signal processing and communication systems.

Learning Objectives

After successfully completing this course, students will be able to

· Characterize probability models using probability density (mass) functions and cumulative distribution functions.

· Characterize random vectors using joint probability density (mass) functions.

· Determine expectations and moments of probability density functions.

· Describe conditional probability distributions.

· Characterize functions of random variables.

· Describe random processes and conditions for stationarity and ergodicity.

· Determine the autocorrelation and spectral density of stationary random processes.

· Analyze the response of LTI systems driven by a stationary random process using autocorrelation and power spectral density.

· Analyze mean square estimation and maximum likelihood estimation of signal parameters.

· Analyze the performance of signal detection systems using binary hypothesis testing.

· Use MATLAB to study and analyze random signal.

Pre-requisite: Probability and Statistics in Engineering, admission to MSEE Program.

BEE 215: Fundamentals of Electrical Engineering

B EE 215, Fundamentals of Electrical Engineering, is a first course in the theory of circuit analysis, which is a fundamental skill required of all electrical engineers. You will learn the "alphabet" of circuits, including wires, resistors, capacitors, inductors, independent and dependent voltage and current sources, and operational amplifiers. This course is essential preparation for anyone needing more than a surface understanding of electrical circuits, and the gateway to advanced electrical engineering courses.

Learning Objectives:

By the end of this course, you will be able to:

1. Identify linear systems and represent those systems in schematic form;

2. Apply Kirchhoff's current and voltage laws and Ohm's law to circuit problems;

3. Simplify circuits using series and parallel equivalents and using Thévenin and Norton equivalents;

4. Perform node and loop analyses and set these up in standard matrix format;

5. Identify and model first-order and second-order electric systems involving capacitors and inductors; and

6. Predict the transient behavior of first and second order circuits.

7. Simulate circuit behavior using modeling tools, such as LTSpice, from Linear Technology Corporation, or Multisim from National Instruments.

Pre-requisites

To take this course, you must already have taken the following courses:

• PHYS 122, or equivalent, and

• either MATH 126, MATH 129, or MATH 136, or equivalent courses.

and the following topics:

• physics of electricity and magnetism

• algebra

• linear algebra and matrices

• trigonometry

• imaginary numbers

• integral and differential calculus

• some exposure to first-and second-order linear differential equations.

BEE 507: Signals and Systems

This course introduces the mathematical representation, analysis and classification of continuous and discrete-time signals and systems. Topics covered include: time domain analysis of Linear Time Invariant (LTI) systems, impulse response, and differential or difference equations; Fourier series and Fourier Transform for continuous and discrete-time signals and systems; Laplace-transform and z-transforms, and their application for system analysis.

Major topics covered in the course include:

1. Description of Continuous and Discrete-time signals and systems;

2. Analysis of input-output relationships of LTI systems;

3. Aiscrete-time Fourier Transform;

4. DFT (FFT) and its applications;

5. Z-transform; and

6. Laplace transform and its applications.

Learning Objectives

After successfully completing this course, students will be able to:

1. Describe and represent discrete-time signals in time domain;

2. Classify discrete-time systems based on various properties;

3. Perform convolutions and analyze LTI systems given an equation that characterizes the system;

4. Solve linear difference equations using classical techniques and z-Transform;

5. Perform frequency-domain analysis of discrete-time signals and systems using Fourier and Laplace transforms; and

6. Use MATLAB to design and analyze filters.

Pre-requisite: B EE 503 (Minimum grade: 3.0).

BEE 515 Digital Image Processing Applications