Edunex 45279, FI6004 Physical Data Processing, Class 01, Academic Year 2022, Semester 2.
- This course is designed to give undergraduate students the concepts of digital processing for data from physical systems.
- It covers Fourier transforms, convolution and deconvolution, digital filtering, signal analysis using auto- and cross-correlations, power spectrum, and transfer function estimation with linear and non-linear regression, and robust estimation.
- Python in Jupyter Notebook, and also available modules and packages, will be used in this course.
- Fourier transforms: Continuous Fourier transform (CFT), discrete Fourier transform (DFT), fast Fourier transform (FFT), cascade decimation, Z-transform, Hilbert transform.
- Convolution and deconvolution.
- Digital filtering: Filter coefficients, low-pass filter, high-pass filter, band-pass filter, moving average, median, robust filters.
- Signal analysis: auto-correlation and cross-correlation, power spectrum.
- Transfer function estimation: linear regression, non-linear regressions, robuts estimation.