Digital Signal Processing
Graduate treatment of discrete-time signals and systems, sampling and reconstruction, z- transforms, transform analysis of linear time-invariant systems, structures for discrete-time systems, filter design techniques, discrete Fourier transform (DFT) and fast Fourier transform (FFT), spectral analysis, and advanced topics.
Course information
New Mexico State University EE545 Digital Signal Processing (3 credits).
Prerequisites
EE311 Signals and Systems or equivalent undergraduate course. Students will be automatically dropped without this prerequisite. EE395 Introduction to DSP or equivalent undergraduate course is strongly recommended.
Textbooks
- Discrete-Time Signal Processing, 2/E by Alan V. Oppenheim, Ronald W. Schafer, and John R. Buck (ISBN 0-13-754920-2)
- DSP Software Toolkit by Phillip L. De Leon
Course Objectives
The objective of this course is to gain an understanding of digital signal processing:
- Discrete-time signals and systems
- Sampling of continuous-time signals
- z-transform analysis of linear, shift-invariant systems
- Digital filter design techniques and filter structures
- Discrete Fourier Transform, Fast Fourier Transform, and spectral analysis
This objective is achieved through a graduate-level treatment of digital signal processing including both theoretical and experimental work.
Course materials
New Mexico State University EE545 Digital Signal Processing lecture notes, homework and solutions, laboratories, and exams.
- Lecture Notes
- Homework and Solutions
- Old Exams
This page is intended as a stable home for official course documents and high-level information.
- Review of discrete-time signals and LTI systems (advanced perspective)
- z-transform and system function analysis
- Pole-zero analysis and stability
- Multirate signal processing (decimation and interpolation)
- Discrete-Time Fourier Transform (DTFT)
- Discrete Fourier Transform (DFT)
- Fast Fourier Transform (FFT) algorithms
- Short-Time Fourier Transform (STFT)
- Spectral analysis and interpretation
- Adaptive Signal Processing
- Digital Speech Processing
- Real-Time Digital Signal Processing