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ECE

ENEE425 Digital Signal Processing

Course Description:  Sampling as a modulation process, aliasing, the sampling theorem, the Z-transform and discrete-time system analysis, direct and computer-aided design of recursive and nonrecursive digital filters, the Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT), digital filtering using the FFT, analog-to-digital and digital-to-analog conversion, effects of quantization and finite-word-length arithmetic

Prerequisite(s): ENEE 322 and completion of all lower division courses

Corequisite(s): None

Course Objectives:

  • Understand how analog signals are represented by their discrete-time samples, and in what ways digital filtering is equivalent to analog filtering
  • Master the representation of discrete-time signals in the frequency domain, using the notions of z-transform, discrete-time Fourier transform (DTFT) and discrete Fourier transform (DFT)
  • Learn the basic forms of FIR and IIR filters, and how to design filters with desired frequency responses
  • Understand the implementation of the DFT in terms of the FFT, as well as some of its applications (computation of convolution sums, spectral analysis)

Topics Covered:

  • Uniform sampling: sampling as a modulation process; aliasing; ideal impulse sampling; sampling theorem; sampling bandpass signals
  • Data reconstruction by polynomial interpolation and extrapolation: zero-order hold; first order hold; linear point connector
  • The z-transform: definition; inverse; useful transform relationships; Parseval's theorem; difference equations
  • Analysis of sampled-data systems by transform methods: transfer functions for discrete-time systems; sinusoidal steady-state frequency response; structures for realizing transfer functions; stability; decimation and interpolation
  • The design of transfer functions for digital filtering: bilinear transformation method for IIR filters; Fourier series, windowing and the Remez algorithm for FIR filters
  • Effects of quantization and finite word length arithmetic in digital filters
  • The discrete Fourier transform (DFT): definition of the DFT and its inverse; transform relationships; cyclic convolution and correlation; fast Fourier transform (FFT); filtering long sequences using the FFT