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Course Syllabus ECE 351 – Linear Systems II Department of Electrical & Computer Engineering 1. Course Number and Name: 2. Credit Units/Contact Hours: 3. Course Coordinator: ECE 351 – Linear Systems II 3/3 Sharlene Katz 4. Text, References & Software Recommended Text: Lathi BP: Linear Systems and Signals, Oxford University Press, 2nd edition, 2004, ISBN 0195158334. Software: MATLAB Internet Resources: http//hpme12.me.edu/matlab/html/ 5. Specific Course Information a. Course Description Continuation of ECE 350, with concentration on discrete system models. Techniques developed include Z-transforms, Fourier Analysis, impulse response, convolution, and state variables for discrete linear systems b. Prerequisite by Topic Students taking this course should have complete familiarity with the topics of Linear System I (ECE350). These include Differential Equations, Laplace Transform, Convolution, Impulse Response, Fourier Series, Fourier Transform and System Analysis using State Variables. c. Required Course 6. Specific Goals for the Course a. Specific Outcomes of Instructions – After completing this course the students should be able to: 1. Classify discrete-time systems as linear or non-linear, causal or anticipatory, time-invariant or time-varying, and stable or unstable; classify digital filters as FIR or IIR; classify discrete-time signals as causal or anticipatory, energy signals or power signals, and periodic or non-periodic, and find the period of a periodic signal; 2. Plot discrete-time signals and compute their energy or power; 3. Apply time domain techniques in the analysis of discrete-time systems; 4. Apply transform domain techniques in the analysis of discrete-time systems and in the design of digital filters; 5. Apply the Nyquist Sampling Theorem in converting continuous-time signals to discrete-time signals, and apply the Discrete Fourier Transform (DFT) in signal analysis; 6. Relate the impulse response, the difference equation, the simulation diagram, and the system transfer function for a linear, time-invariant discrete-time system; 7. Design FIR and IIR digital filters (low-pass, high-pass, band-pass and notched) 8. Use MATLAB to perform simple signal processing tasks (as indicated in learning outcomes 2-5, 7 and 8) for discrete-time signals and discrete-time linear systems b. Relationship to Student Outcomes This supports the achievement of the following student outcomes: a. An ability to apply knowledge of mathematics, science, and engineering to the analysis of electrical and computer engineering problems. b. An ability to design and conduct scientific and engineering experiments, as well as to analyze and interpret data. c. An ability to design systems which include hardware and/or software components within realistic constraints such as cost, manufacturability, safety and environmental concerns. e. An ability to identify, formulate, and solve electrical and computer engineering problems. k. An ability to use modern engineering techniques for analysis and design. n. Knowledge of mathematics including differential equations, linear algebra, complex variables and discrete math. 7. Topics Covered/Course Outline 1. Sampling and Digital Signaling/System Advantages 2. Discrete-time Signal Models and the Impulse Response 3. Convolution 4. Difference Equations 5. Simulation Diagrams and System Stability 6. Z-Transforms 7. System Transfer Functions 8. Pole-Zero Diagrams and the Frequency Response 9. Digital Filter Design 10. DFT’s and FFT’s 11. State Space Models Prepared by: Sharlene Katz, Professor of Electrical and Computer Engineering, October 2011 Ali Amini, Professor of Electrical and Computer Engineering, March 2013