This course presents a simple and informal discussion of the fundamental concepts which underlie the quantitative part of geophysical analysis and interpretation. These general concepts are applicable for an analytical approach to any phenomena that can be measured and recorded and includes examples and exercises created and analysed using Microsoft Excel®.
The course is generally for anyone with an interest in learning or refreshing their understanding of the fundamentals of signal processing.
Prerequisites (Knowledge/Experience/Education required)
Basic high school algebra and trigonometry, some experience with Excel or other spread-sheet applications and a keen interest in learning.
Who Should Attend?
The course is designed for students in the sciences as well as professionals who work with and support geophysicists. The course will be valuable for geologists, junior seismic interpreters, software developers, high school and university students, and geophysical professionals seeking a refresher of the basic concepts.
- What is a signal?
- A simple signal
- The sine function as signal
- More complicated signal
- Fourier analysis
- Digital signals
- Discrete Fourier transform
- Digital filtering
- Signals and noise
- Practical filter example
- Measurement domain processes
Topics covered include: the concept of signals based on the sine function; the summation of sine waves as a more complicated signal; the notion of Fourier series and the spectral representation of signals; digital sampling and discrete representation of signals; the discrete Fourier transform and inverse transform; the concept of filtering in the spectral domain; and the idea of filtering outside of the spectral domain, by convolution, and the relationship between the measurement and spectral domains.
- Define a simple signal and its characteristics
- Describe the components of a compound signal
- Differentiate between and explain measurement and spectral domains
- Describe the difference between analog and digital signals
- Solve for appropriate digital signal sampling attributes
- Contrast between signal and noise
- Employ simple spreadsheet algorithms to filter signals
- Compare measurement and spectral domain complementary processes