Python Applications for Digital Design and Signal Processing

Fall 2019 Course

Date: Thursday, and Friday, September 26 and 27, 2019

Time: 8:30AM – 5:00PM

Decision date: Monday, September 16, 2019

Early Registration Date deadline:  Friday, September 6, 2019

Click here to register:

Before Early Registration Date:

Members: $450
Non-members: $495

After Early Registration Date:

Members: $515
Non-members: $535

Notes, Lunch and Coffee Breaks included with registration!

WHERE: Crowne Plaza Hotel, Woburn
15 Middlesex Canal Park Road

Phone 781-245-5405

Speaker: Dan Boschen

Course Summary:

This is a bring-your-own laptop, hands-on course in the popular and powerful open source Python programming language.

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 solving signal processing challenges. Students will be using the Anaconda distribution, which combines Python with the most popular data science applications, and the 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.

Once a basic working knowledge of the language is established, 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.

Jupyter Notebooks: This course makes extensive use of Jupyter Notebooks which combines running Python code with interactive plots and graphics for a rich user experience. Jupyter Notebooks is an open-source web-based application (that can be run locally) that allows users to create and share visually appealing documents containing code, graphics, visualizations and interactive plots. Students will be able to interact with the notebook contents and use “take-it-with-you” results for future applications in signal processing.

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Target Audience: This course is targeted toward users with little to no prior experience in Python, however familiarity with other modern programming languages and an exposure to object-oriented constructs is very helpful. Students should be comfortable with basic signal processing concepts in the frequency and time domain. Familiarity in Matlab or Octave is not required, but the equivalent operations in Python using the NumPy package will be provided for those students that do use Matlab and/or Octave for signal processing applications.

A laptop (Mac or PC) preconfigured with Anaconda is required; the specific installation instructions will be emailed to students prior to the start of class.

Biography:

Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems. Dan is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions.

For more background information, please view Dan’s Linked-In page.

Thursday, September 26

8am-8:30am Registration/sign-in, coffee

8:30am-10am Topic 1: Intro to Jupyter Notebooks, the Spyder IDE and the course design examples including Delta Sigma Converters, GPS Code Generators, and Numerically Controlled Oscillators. Core Python constructs.

15 minute break

10:15am-12:00 pm Topic 1, continued.

45 minute lunch

12:45pm-2:45pm Topic 2: Core Python constructs, functions, reading writing data files.

15 minute break

3:00pm-5:00pm Topic 2, continued.

Friday, September 27

8:30am-10am Topic 3: Signal processing simulation with popular packages including NumPy, SciPy, and Matplotlib.

15 minute break

10:15am-12:00 pm Topic 3, continued.

45 minute lunch

12:45pm-2:45pm Topic 4: Bit/cycle accurate modelling and analysis using the design examples and simulation packages

15 minute break

3:00pm-5:00pm Topic 4, continued, Final questions.