ECE 4250 - Digital Signal and Image Processing


     
Spring. 4 credits. Letter grades only.

Prerequisite:  ECE 3250 .  Culminating design experience (CDE) course.

Staff.

Introduces statistical signal processing. Signal representation and manipulation are covered via correlation and using the DFT/FFT to estimate other transforms; applications of these topics are then covered, including quantization, quantization effects in digital filters, multirate DSP, filter banks, delta-sigma modulation, power spectrum estimation, and introductions to Wiener and Kalman filtering and image processing.

Outcome 1: Be able to draw Fourier spectra in both discrete-time frequency and continuous-time frequency,
while undergoing common operations such as filtering, upsampling, downsampling, A/D and D/A.

Outcome 2: Given a finite-duration, discrete-time signal, be able to estimate the discrete-time Fourier
Transform and the original frequency content in the signal (e.g., the continuous-time Fourier
Transform) and give bounds on the accuracy of the estimate.

Outcome 3: Given a continuous-time signal with certain frequency- and time-based characteristics, be able to design a (real-world, non-ideal) system to appropriately sample the signal such that desired characteristics are maintained to within given tolerances.

Outcome 4: Given a digital audio (1-d) or image (2-d) signal, be able to select an appropriate frequency-
based transform suitable for the desired or specified processing.

Outcome 5: Quickly prototype and debug signal processing algorithms using Matlab.



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