EECE 491 Syllabus, Fall 2015

Department of Electrical and Computer Engineering American University of Beirut EECE 491 ⎯ Discrete-Time Signal Processing Course Information Catalog description: Digital Signal Processing (DSP) is at the heart of almost all modern technology. This course introduces the fundamentals of DSP systems, including properties of discrete-time linear systems, digital filter design, sampling and reconstruction, A/D and D/A conversion, quantization, discrete-time Fourier analysis, spectral analysis, sample- rate conversion, FFT and fast convolution, filter structures and realizations, and multirate DSP and filter banks. The course also discusses applications of DSP in areas such as speech/audio processing, autonomous vehicles, and software radio. It includes a project related to implementations of DSP applications on embedded processors. Credit hours: 3 credits Required or elective: Elective for ECE and CCE students. Prerequisites: − By course: EECE 340 (Signals and Systems Course) − By topic: Basic knowledge in signals and systems. Textbook: − A. Oppenheim and R. Schafer, Discrete-Time Signal Processing, 3rd ed., Pearson Education, 2009, ISBN 978-0131988422. References: − J. Proakis and D. Manolakis, Digital Signal Processing, 4th ed., Pearson Education, 2007, ISBN: 9780131873742. − S. Mitra, Digital Signal Processing: A Computer-Based Approach, 4th ed., McGraw-Hill, 2011, ISBN: 978-0077366766. − C. Johnson, Jr., W. Sethares, and A. Klein, Software Receiver Design, Cambridge University Press, 2011, ISBN 978-0521189446. − T. Welch, C. Wright and M. Morrow, Real-Time Digital Signal Processing from MATLAB to C with the TMS320C6x DSPs, CRC Press, 2nd ed., 2011, ISBN 978-1439883037. Computer usage: − Simulink, Matlab DSP/Audio/Communication toolboxes − TI embedded processor development kit Course Objectives − Develop skills for analyzing and synthesizing algorithms and systems that process discrete time signals, with emphasis on realization and implementation. − Explain the theory and concepts behind the operation and construction of DSP systems. − Analyze basic DSP building blocks including: analog-to-digital (A/D) and digital-to-analog (D/A) converters, digital filters, spectrum analyzers, sample rate converters (up-sampling and down- sampling), and the fast Fourier transform (FFT) algorithm. − Design digital filters to meet target magnitude and phase responses. − Design and implement these building blocks and use them effectively in applications. − Evaluate DSP systems and justify choices among alternative designs. Course Topics − DSP overview: Signals, systems, and transforms − Fourier series and transforms: Continuous-time (CT) Fourier series; discrete-time (DT) Fourier series; CT Fourier transform; DT Fourier transform; discrete Fourier transform (DFT) − DFT spectral analysis − Sampling, A/D and D/A converters − LTI discrete-time systems in the transform domain: Impulse response, convolution, difference equations, z-transform, system analysis, BIBO stability. − Frequency response of LTI systems: lowpass, highpass, and Bandpass Filters − Linear-phase, generalized linear phase, and minimum-phase systems − DT processing of CT systems − Digital filter structures and realizations − IIR digital filter design: bilinear transformation and impulse invariance − FIR digital filter design: truncation, windowing, frequency sampling, optimal min-max filter design − Down-sampling, up-sampling, and oversampling A/D and D/A − Digital interpolation and noise shaping − Fast Fourier transform (FFT), fast convolution − Introduction to multi-rate DSP and multi-rate filter banks − Quantization effects in fixed-point implementations of filters − Practical implementations of DSP applications on embedded processors Course Learning Outcomes Upon successfully completing this course, the student should: − Be familiar with the terminology that is used in the DSP field − Understand the basics of DT-LTI systems − Understand how to sample continuous-time signals. − Know how to perform discrete-time processing of continuous-time signals. − Know how to perform continuous-time processing of discrete-time signals. − Determine what the best discrete-time filters are. − Know how to design FIR and IIR DSP filters. − Be able to analyze the effect of finite-precision on numerical and hardware implementation. − Determine the relationship between the Fourier transform, Fourier Series, Discrete Fourier Transform, and the Fast Fourier Transform. − Understand how to use the Discrete Fourier Transform to analyze continuous time signals. − Understand the decimation-in-time and decimation-in-frequency FFT algorithms. − Know how to do fast convolution using the FFT. − Understand the basics of downsampling and upsampling, oversampling A/D and D/A, digital interpolation, and noise shaping. − Know how to design a basic multirate filter bank. Class schedule: Two 75-minute lectures or three 50-minute lectures per week Evaluation methods 1. Homework 10% 2. Project 20% 3. Midterm(s) 35% 4. Final Exam 35% Professional component: Engineering topics: 100% Person(s) who prepared this description and date of preparation Mohammad M. Mansour, September 2015 Date of last revision: September 2015