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Dr. Gary L. Dempsey

Academic Courses

EE 431 - Control System Theory I (Fall)

Course Description: The course consists of modeling electrical, mechanical, hydraulic and thermal systems, analysis of linear systems in the time and frequency domains, stability concepts and compensation design in the time and frequency domains. Classical control will be emphasized. The software programs MATLAB and the Controls System Toolbox will be incorporated into the lectures, homework, and tests.

EE 450 – Electronic Product Design (Fall)

Course Description: The objective of the seven week laboratory course is to assess student design abilities in the analog, digital, microcontroller interfacing and programming areas. Design to product specifications is a critical item that is addressed in the course. The students will examine two product designs in the course. The first product is a Simulink model of a DC motor controlled via a joystick. Experimental data will be compared with the model developed in Simulink (1 week). The second product, the mini-project, is microcontroller-based (5 weeks). A new product and set of specifications are developed each year for the mini-project. The seventh week of the course is used to complete the mini-project final report and laboratory notebook. See mini-project for current and past year’s projects.  The EE 450 course was developed to prepare students to work at the professional level for their senior capstone project. Expectations for the capstone project design work can be observed in the Professional Level document.
 

 EE 535 - Engineering Applications of Neural Networks (Spring)

Course Description: The course will provide the student with a working knowledge of the theory, design and applications of artificial neural networks. Emphasis is directed to low-level implementation such as embedded microcontrollers and integrated circuits. Specific architectures such as correlation matrix memory, perceptron, adaline, CMAC, multilayer networks, and Hopfield networks will be examined as well as their corresponding learning rules. Application areas such as control systems, optimization networks and image, signal, and speech processing will be discussed. The engineering simulation program MATLAB and its Neural Network Toolbox will be incorporated into the lectures and homework. Homework projects will allow the students to explore several neural applications.

EE 432 - Control System Theory II (Spring)

Course Description:The course consists of modeling electrical, mechanical, hydraulic and thermal systems, analysis of linear systems in the time and frequency domains, stability concepts and compensation design in the time and frequency domains. State-variable and digital control methods will be emphasized. The software program MATLAB (Controls Toolbox) will be incorporated into the lectures and homework.

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 Last modified December 31, 2006