Catalog Description: Discrete time signals and systems: Fourier and Z transforms, DFT, 2-dimensional versions. Digital signal processing topics: flow graphs, realizations, FFT, chirp-Z algorithms, Hilbert transform relations, quantization effects, linear prediction. Digital filter design methods: windowing, frequency sampling, S-to-Z methods, frequency-transformation methods, optimization methods, 2-dimensional filter design.
Units: 4
Prerequisites: EL ENG 120
Formats:
Fall: 3 hours of lecture, 1 hour of discussion, and 1 hour of laboratory per week
Spring: 3 hours of lecture, 1 hour of discussion, and 1 hour of laboratory per week
Grading basis: letter
Final exam status: Written final exam conducted during the scheduled final exam period
Class Schedule (Spring 2023):
TuTh 17:00-18:29, Moffitt Library 101 –
Gopala Anumanchipalli
Department Notes:
Course objectives: To develop skills for analyzing and synthesizing algorithms and systems that process discrete time signals, with emphasis on realization and implementation.
Topics covered:
- Signal Processing and its Applications
- LTI, Discrete Time Fourier Transform
- Symmetry properties of DTFT, Convergence of DTFT
- Sampling, Downsampling
- Upsampling
- Region of Convergence for Z.T.
- C.R.T. To Compute Inverse Z.T.
- Difference Equations and LTI Systems
- Realizations of L.C.C.D.E.
- Realizations of IIR Filters with Rational Transfer Function
- Cascade + Parallel Implementation of ± IR Filters with Rational Transfer Function
- Realization of FIR Filters
- Linear Phase Filtering
- Conditions for Achieving Linear Phase
- Filter Design
- FIR Filter Design using Windows
- Optimum FIR Filter Design
- Algorithms for Optimal Filter Design
- IIR Filter Design
- IIR Filter Design Transformation, Discrete Fourier Series, and DFT = Discrete Fourier Transform
- Properties of DFT
- Using DFT to do Linear Convolution
- Fast Fourier Transform
- FFT: Decimation in Frequency
- DCT and its Relation to DFT
Related Areas: