Available courses

Survey of modern approaches to estimating the state of linear and nonlinear dynamic systems. Topics include linear systems theory, the Kalman filter, the extended Kalman filter, unscented Kalman filter, and the particle filter. Lectures and assignments will include theory, implementation, and applications of these methods. Designed to give a solid introduction and fundamental understanding of the advantages, limitations, and tradeoffs for each of these methods.
Unified introduction to the theory, implementation, and applications of statistical signal processing methods. Focus on estimation theory, random signal modeling, characterization of stochastic signals and systems, and nonparametric estimation. Designed to give a solid foundation in the underlying theory balanced with a discussion of the practical advantages and limitations of nonparametric estimation methods.
Unified introduction to the theory, implementation, and applications of statistical signal processing methods. Focus on optimum linear filters, least squares filters, the Kalman filter, signal modeling, and parametric spectral estimation. Designed to give a solid foundation in the underlying theory balanced with examples of practical applications and limitations.
Experimental laws, network theorems, and computer analysis techniques of electrical circuit analysis. Network responses to various forcing functions using time-domain and phasor-domain methods.
Engineers always have, and in today’s technology heavy world, increasingly are founding companies and taking on CEO roles of small, high growth companies. This course will help prepare engineers for a career as a company founder, part of a founding team, or a CEO of a small company. Topics covered will be ones that are essential for creating a company that can first sustain, then be profitable, then develop a strategy for high growth, and finally be the kind of company that can have M&A options that include raising capital or selling the company. The importance of people and culture and why and how successful companies always have viewed them as essential will be a critical topic covered throughout this course.
Course Description: Introduction to the Laplace Transform for circuit analysis. Design of analog filters, transfer function analysis, Bode plot analysis, and pole-zero diagrams.

Prerequisite: ECE 221 & ECE 201
Introduction to continuous time and discrete time systems. Thorough exposure to the Laplace transform for circuit and system analysis, transfer functions, bode plots, analog filters, and two-port networks.

Prerequisite: ECE 221, ECE 201; Mth 256 or concurrent.
Continuous-time and discrete-time Fourier series, continuous-time Fourier transform, discrete-time Fourier transform, fast Fourier transform, sampling, aliasing, communications, modulation, discrete-time filters.

Prerequisite: ECE 222.