Machine Learning for EW

Course Length: 14 hours total - delivered across 2 day sessions of 7-hours each.

Saturday & Sunday, 09:00 – 17:00 EDT (13:00 - 22:00 UTC), October 26th – October 27th

Description:

This course introduces students to the fundamentals of machine learning and its application to modern Electronic Warfare (EW) and cyber solutions. Commencing with an overview of machine learning, and its recent evolution into deep learning, the course focuses on providing an education in how these algorithms work and training on how to apply them in an EW context. As an example, machine learning using neural networks will be discussed, followed by a demonstration on how to implement one to solve a classification problem using Electronic Intelligence (ELINT).

The course contains four major topics: introduction to machine learning, classification using neural networks, training machine learning systems for EW, and developing solutions using machine learning for EW. Each topic will include lectures, demonstrations, and, for the more ambitious, an exercise to further explore the capabilities of machine learning in EW and cyber applications.

Course Outline:

Time	Day 1	Day 2
09:00 - 09:40	Introduction	Radar Waveforms
09:50 - 10:30	Understanding Machine Learning	Communications Waveforms
10:40 - 11:20	Probability Models	Deep Learning
11:30 – 12:10	Regression	Lab – Generating Training Data
12:10 – 13:00	LUNCH	LUNCH
13:00 – 13:40	Classification	Cognitive Electronic Warfare
13:50 – 14:30	Neural Networks	Classifying Electronic Intelligence
14:40 – 15:20	Machine Learning Tools	Lab – Classifying ELINT
15:30 – 16:10	Lab – Developing a Neural Network	Lab – Classifying ELINT
16:20 – 17:00	Lab – Developing a Neural Network	Conclusion

This course is held in conjunction with the 56th Annual AOC International Symposium & Convention, held October 28-30, 2019 in Washington D.C. Registration for that event does not constitute registration for this course, nor are there any connected costs or discounts.

This course will be held on-site for two days prior to this year's symposium and convention. Beverages will be provided to attendees, but meals are your own responsibility.

Maximize your time at the 2019 AOC Convention by adding Kyle Davidson's follow-up course!
Sign up for "Electronic Countermeasures: Theory and Design" being offered on October 31 - November 1.

Who should attend:

The intended audience of this course are Electronic Warfare (EW) professionals looking to expand their knowledge of the field and machine learning. No prior experience in EW is required, but a background in engineering or science is recommended.

Speaker and Presenter Information

Instructor: Kyle Davidson

Kyle Davidson is a former signals officer, having served for 15 years in the Canadian Army. During this time, he held a variety of positions in the field force, on operations in Afghanistan, and as an educator. For the last five years in the Army he served at the Royal Military College of Canada (RMC) as an assistant professor in the Department of Electrical and Computer Engineering, from which he holds a B.Eng. and M.A.Sc. He continues to serve as an adjunct professor at RMC and is scheduled to defend his Ph.D. in EW systems engineering in the spring of 2019. Since leaving the Canadian Armed Forces he has worked as a Radar and Electronic Warfare Scientist and later Head of Capability at Tactical Technologies Inc., a subsidiary of Leonardo MW, on a variety of projects, often related to the Eurofighter Typhoon's defensive aid suite. He is currently the Chief Engineer for Electronic Warfare Systems at MDA where he focusses on developing EW technologies and teams to support a variety of projects in the land, air, sea, and space domains.