

ECE 4250  Digital Signal and Image ProcessingSpring. 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, deltasigma modulation, power spectrum estimation, and introductions to Wiener and Kalman filtering and image processing. Outcome 1: Be able to draw Fourier spectra in both discretetime frequency and continuoustime frequency, while undergoing common operations such as filtering, upsampling, downsampling, A/D and D/A. Outcome 2: Given a finiteduration, discretetime signal, be able to estimate the discretetime Fourier Transform and the original frequency content in the signal (e.g., the continuoustime Fourier Transform) and give bounds on the accuracy of the estimate. Outcome 3: Given a continuoustime signal with certain frequency and timebased characteristics, be able to design a (realworld, nonideal) system to appropriately sample the signal such that desired characteristics are maintained to within given tolerances. Outcome 4: Given a digital audio (1d) or image (2d) 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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