Seminar: Digital Signal Processing Refresher
Digital Signal Processing Refresher is a 2.5-day seminar reviewing basic digital signal processing (DSP) theory and techniques. It is intended for engineers and software developers with some previous DSP exposure, but needing a review and update to their skills; or for a fast introduction to DSP for technical personnel new to the area. It presumes some prior familiarity with basic linear systems concepts such as filtering and Fourier transforms, but does not require extensive prior experience.
Participants receive a soft-cover notebook containing hard copy of all seminar slides, as well as a CD with PDF files of all slides.
The seminar is offered on a consulting or fee-for-service basis. Participation does not earn any Continuing Education Units (CEUs) or other accredited credentials.
Following is an outline of the seminar content. (Note: this outline is subject to update and change.) For additional information, including pricing, availability, and other available seminars, please contact Dr. Richards.
Topical Outline for Digital Signal Processing Refresher
Participants receive a soft-cover notebook containing hard copy of all seminar slides, as well as a CD with PDF files of all slides.
The seminar is offered on a consulting or fee-for-service basis. Participation does not earn any Continuing Education Units (CEUs) or other accredited credentials.
Following is an outline of the seminar content. (Note: this outline is subject to update and change.) For additional information, including pricing, availability, and other available seminars, please contact Dr. Richards.
Topical Outline for Digital Signal Processing Refresher
- Fourier Transforms
- Sampling and Aliasing
- Discrete Fourier Analysis
- Discrete-Time Fourier Transform
- Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT)
- Windowing
- DFT Spectral Analysis
- Linear Systems and Convolution
- Digital Filters
- Finite Impulse Response (FIR) Filters
- Infinite Impulse Response (IIR) Filters
- Random Signals and Noise
- Random Signals in Linear Systems
- Noise
- Signal and Filter Coefficient Quantization
- Integration and Signal-to-Noise Ratio (SNR)
- Reconstruction and Interpolation
- Computational Complexity