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Python Applications for Digital Design and Signal Processing
September 27 @ 6:00 pm - 7:30 pm
First Video Release, Wednesday, September 7, 2022. Additional videos released weekly in advance of that week’s live session!
Live Workshops: 6:00PM – 7:30PM EDT, Tuesdays, September 13, 20, 27, October 4
Attendees will have access to the recorded session and exercises for two months (until December 4) after the live session ends!
This is a hands-on course combining pre-recorded lectures with live Q&A and workshop sessions in the popular and powerful open-source Python programming language.
New Format with Pre-Recorded Videos: The course format has been updated to release pre-recorded video lectures that students can watch on their own schedule, and an unlimited number of times, prior to live Q&A workshop sessions on Zoom with the instructor. The videos will also be available to the students for viewing for up to two months after the conclusion of the course.
Overview: Dan provides simple, straight-forward navigation through the multiple configurations and options, providing a best-practices approach for quickly getting up to speed using Python for modelling and analysis for applications in signal processing and digital design verification. Students will be using the Anaconda distribution, which combines Python with the most popular data science applications, and Jupyter Notebooks for a rich, interactive experience.
The course begins with basic Python data structures and constructs, including key “Pythonic” concepts, followed by an overview and use of popular packages for scientific computing enabling rapid prototyping for system design.
During the course students will create example designs including a sigma delta converter and direct digital synthesizer both in floating point and fixed point. This will include considerations for cycle and bit accurate models useful for digital design verification (FPGA/ASIC), while bringing forward the signal processing tools for frequency and time domain analysis.
Speaker(s): Dan Boschen ,
Tuesday, September 13
Topic 1: Intro to Jupyter Notebooks, the Spyder IDE and the course design examples. Core Python constructs.
Tuesday, September 20
Topic 2: Core Python constructs; iterators, functions, reading writing data files.
Tuesday, September 27
Topic 3: Signal processing simulation with popular packages including NumPy, SciPy, and Matplotlib.
Tuesday, October 4
Topic 4: Bit/cycle accurate modelling and analysis using the design examples and simulation packages