ETEG 305 
ETEG 305 DIGITAL SIGNAL PROCESSING 3 Credits Objectives: To introduce digital signal processing techniques and applications. Syllabus: Review of Signal and Systems course regarding discretetime signals and systems ZTransform: Definition of the ztransform, relation between the Ztransform and the Fourier transform of a sequence, properties: linearity, shifting, convolution, scaling, multiplication by K Vector sequences; Inverse ztransform: direct division, partial fraction expansions, the inverse integral; System response, transfer function H(z), transient and steady state sinusoidal response  polezero relationships, stability. Discrete filters: Filter structures, second order sections, ladder and wave filters; Frequency response; Sampling continuous signals, spectral properties of continuous signals, aliasing, antialiasing signals and reconstruction analog filters; Effects of sample and hold at filter input and output; Digital filters, finite precision implementations of discrete filters; Scaling & noise in digital filters, quantized signals, quantization error, linear models Finite Duration Impulse Response (FIR) Digital Filters: FIR filter design by Fourier approximation, the complex Fourier series, Gibbs phenomena in FIR filter design approximations, applications of window functions to frequency response smoothing; Window functions, rectangular, Hanning, Hamming and Kaiser windows; FIR filter design by the frequency sampling method; FIR filter design using the Remez exchange algorithm; Linear phase FIR filters, unit sample response symmetry, group delay. Infinite Impulse Response (IIR) Digital Filters : Classical filter design using polynomial approximations, Butterworth, Chebychev, elliptic and Bessel forms, IIR filter design by transformationmatched Ztransform, impulseinvariant transform and bilinear transformation, application of the bilinear transformation to IIR lowpass discrete filter design, spectral transformation, highpass, bandpass and notch filters The Discrete Fourier Transform: The discrete Fourier transform (DFT) derivation, properties of the DFT, DFT of nonperiodic data, use of window functions Introduction of the Fast Fourier Transform (FFT): FFT computation methods, Spectral analysis and convolution using FFT, Power spectral density using DFT/FFT algorithms Applications of Digital Signal Processing and Introduction to Digital Signal Processors References:
