ME57900 - Fourier Methods in Digital Signal ProcessingSpring 2016
Days/Time: TBA / TBA
Credit Hours: 3
To familiarize the student with functions found in most frequency analysis software, introduce the basics of digital filtering and digital filter design, introduce basis of stationary signal analysis and derive input-output relationships for linear time-invariant systems.
Alternate Title: Fourier Methods in Digital Signal ProcessingFundamentals of signal processing associated with Fourier analyzer systems are presented. Emphasis is on amplitude accuracy and frequency resolution properties necessary for reliable experimental methodologies in system identification, spectrum estimation, and correlation analysis. Deterministic as well as random data analyses are presented.
Engineering applications of Fourier analysis of signals, both random and deterministic; Digital Filtering; Spectral estimation; Transfer function estimation; Coherence; Effects of measurement (windowing, sampling, noise); Strategies to minimize adverse effects and to facilitate meaningful interpretation of data analysis results
Undergraduate treatment of Laplace transforms, Fourier series, basic statistics.
Five to seven homework assignments, each consisting of 5 to 7 questions. Please keep each problem separate, i.e. start a new problem on a new sheet of paper, and make sure your name and the problem set and problem number are on each sheet of your solutions.
One midterm exam and one final exam.
Required-None. List of recommended reference texts will be provided with the course syllabus.
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ProEd minimum computer requirements, Pentium or equivalent required, 0.1 Gigabytes of disk space, MATLAB with the signal processing toolbox; extensive use of MATLAB, including use of MATLAB programs and programming of specific algorithms used during homeworks (note: some functions used during class are not available in the student edition of MATLAB); must be compatible with Microsoft packages; course outline and information, homeworks and solutions, signals for downloading for homework, sample exams and exam solutions, projects, grades, pointers to course references and exam announcements will be posted on the course web site.
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As noted previously, access to MATLAB and the signal processing, system identification and statistics toolboxes.