Sign-in Links
ELEC 421 Digital Signal Processing Units: 4.00
Sampling theorem, discrete and fast Fourier transform, filter realization structures, quantization errors, finite and infinite impulse response filter design techniques. LMS adaptive filtering, Wold decomposition and spectral modeling, linear prediction. Experiments use Matlab to model and process random signals.
(Lec: 3, Lab: 0.5, Tut: 0.5)
(Lec: 3, Lab: 0.5, Tut: 0.5)
Offering Term: W
CEAB Units:
Mathematics 0
Natural Sciences 0
Complementary Studies 0
Engineering Science 24
Engineering Design 24
Offering Faculty: Smith Engineering
Course Learning Outcomes:
- Analyze pole-zero filters using z-transforms and relate to their time- and frequency-domain properties.
- Analyze, design, and specify computational algorithms for real-time realizable digital filters.
- Understand the theory of adaptive finite impulse response filters.
- Understand the principle of modeling random signals using digital filters and the theory of linear prediction.
- Write software to implement adaptive filtering algorithms for noise cancellation and test the theory of LMS adaptive filters.
- Write software to test linear prediction for all-pole modeling of random processesand apply that to speech synthesis.