Course SCI104
Signal Processing with Python Using Numpy and Scipy
Signal Processing with Python Using Numpy and Scipy
Duration: 2 Days
Synopsis
This course provides an intensive overview of accessing signal processing software from the Python, numpy, scipy perspective. The emphasis is on using Python's expressiveness and "glue language" capabilities to their maximum extent. There is also an element of "rapid prototyping" involving use of Python modules for data visualisation, parsing and code generation.
Prerequisites
Attendees are expected to have a good working knowledge of Python and a good basic understanding of Digital Signal processing - both the maths and the practiceCourse Outline
Signal and Image Processing with Python
- Basic DSP - Filter_design and filtering (time-domain and frequency-domain, FIR and IIR)
- Block-based (streaming) filtering
- Overview of SciPy tools for linear system analysis and simulation
- Waveform generation
- General N-dimensional filtering (median, order, convolution)
- Advanced DSP techniques - interpolation and sampling
- Kalman filters and time series
- Wavelets
- Image processing using ndimage (morphology, segmentation, filtering, interpolation)
- OpenCV and Python image processing