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Dec 26, 2024
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EE 6713 - Digital Signal Processing
Familiarity with probability and stochastic signals; linear system analysis; basic DSP expected. Review of discrete time signals and systems, the z-transform, sampling. Transform domain analysis. Design of IIR and FIR filters; DFT, FFT, and Fourier analysis, spectrum and eigenanalysis, parametric signal modeling.
Requisites:
Credit Hours: 3
Repeat/Retake Information: May not be retaken.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes:
- Analyze signal spectra, correlations, and eigenvalue structure.
- Analyze systems using the DFT, z-transform.
- Design basic FIR and IIR filters.
- Understand common parametric signal models.
- Understand discrete time analysis of random signals.
- Understand the use and implementation of the DFT and FFT
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