ECE 340: Engineering Systems Analysis

Catalog Data: Engineering Systems Analysis (3) Basic concepts in the modeling and analysis of engineering systems and fundamental topics in communications, controls, and signal processing, includes classification of systems, signal characterization in frequency domain, Fourier and Laplace transforms, representation of continuous-time systems by I/O models, system diagrams, state-variable models, stability analysis and Bode plots, feedback system characteristics, discrete-time systems, and digital signal processing. P320

Textbook: R.E. Ziemer, W.H. Tranter, and D.R. Fannin, Signals and Systems: Continuous and Discrete, 4th edition, chapters 1-8, MacMillan Publishing Company, New York, 1998.

Course Coordinator: Dr. François E. Cellier, Professor of ECE.

Goals: The goal of this course is to provide students with the basic mathematical techniques and tools needed for the analysis of linear continuous-time and discrete-time engineering systems. Application areas include: electrical circuits, mechanical systems, communication systems, and simple thermodynamic phenomena. After completing the course, the student will have a solid understanding of mechanisms and tools that allow to derive mathematical descriptions of linear, time-dependent physical phenomena in both time and frequency domains. ECE 340 is a strong prerequisite to ECE 429, ECE 431, ECE 441, ECE449, and ECE472.

Prerequisites by topic: ECE 320 is a strong prerequisite to this class. No student will be admitted to ECE 340 who has not already completed ECE 320 or an equivalent class offered at another university.

Topics:

  1. Signal classification: continuous-time vs. discrete-time, periodic vs. aperiodic, energy vs. power signals. (3 classes)

  2. Systems modeling and analysis: time-invariance, causality, linearity, system response, convolution integral, system stability. (7 classes)

  3. Fourier series: representation of periodic signals, trigonometric and exponential Fourier series, Parseval's theorem. (6 classes)

  4. Fourier transform: Fourier integral, energy spectral density, theorems, inverse Fourier transform, applications. (7 classes)

  5. Laplace transform: definition, theorems, region of convergence, inverse Laplace transform, relationship to Fourier transform. (3 classes)

  6. Applications of Laplace transform: transfer functions, frequency response, stability, Bode diagram, block diagram. (3 classes)

  7. State-space representation: formulation, equivalence transformations, relationship to transfer function, state transition matrix, solution. (6 classes)

  8. Discrete-time signals and systems: analog-to-digital conversion, sampling rate, aliasing, Nyquist rate, z-transform, theorems, inverse z-transform, discrete transfer function, discrete state-space representation, relationship to discrete transfer function, discrete state transition matrix. (9 classes)

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