Digital Signal Processing

On the successful completion of this course, the student should be able to: 1. specify the sampling, quantization, and signal conditioning requirements for a given DSP application; 2. identify components of a DSP hardware system and program a DSP processor in the C language; 3. estimate spectra of discrete-time signals using the fast Fourier transform (FFT) in MATLAB and implement the FFT on a DSP chip; 4. determine and interpret the z-domain transfer function of a discrete-time system and design discrete time filters in the z domain using the pole-zero method; 5. design finite impulse response (FIR) and infinite impulse response (IIR) discrete-time filters for lowpass, high-pass, bandpass, bandstop, and arbitrary frequency response applications; 6. implement digital filter designs in MATLAB and on a DSP chip; and 7. analyse discrete-time filter banks and multi-rate signal processing systems.

Review of discrete-time signals and systems with emphasis on sampling and quantization. Introduction to DSP hardware architecture, including fixed-point vs. floating-point processors and the multiply-accumulate unit. Convolution and spectral analysis using the discrete-time Fourier transform. The discrete Fourier transform, the fast Fourier transform (FFT), and use of the FFT for convolution and spectral analysis. Z- transforms, pole-zero analysis of discrete-time systems, and pole-zero-based digital filter design. Analysis of FIR and IIR discrete-time systems with emphasis on phase response. Design and implementation of FIR digital filters. Design and implementation of IIR digital filters. Introduction to multi-rate signal processing and filter banks.