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Don't worry. The entire presentation and Q&A will be recorded for viewing approximately 24 hours after the event. You can find the link to the recording in our AOC Virtual Series Archive.  The AOC offers all past webinars for free to members. A password is required to view archived webinars. Members, click here to get your password and start watching right away. Not a member? Click here to sign up, and start viewing the webinars in minutes!

PLEASE NOTE: By registering for this event, the details of your profile may be used by the Association of Old Crows (AOC), the presenter, or the sponsor(s) to contact you by email.

Innovations in Machine Learning and their benefit to Electronic Warfare

Innovations in Machine Learning and their benefit to Electronic Warfare

Thursday, November 02, 2017 14:00 until 15:00 EST
Thursday, November 02, 2017 18:00 until 19:00 UTC

In recent years, there has been a huge acceleration in Machine Learning (ML) and Artificial Intelligence (AI) development. This has taken it from a concept little-appreciated outside of engineering and science circles, to something that we hear about on a daily basis. From driverless cars to intelligent home assistants, these technologies are anticipated to dramatically impact the way we live our lives. But how can we apply machine learning to the field of Electronic Warfare and what benefits will this bring?

This webinar will explore two key problems for operatives analyzing the RF spectrum: signal classification and detection of anomalous signals. Recent innovations mean that machine learning can be used to solve these problems more effectively and efficiently, freeing up operatives for more critical tasks.

Signal classification, including recognition of modulation type, is a complex problem which can be solved much more successfully with the use of trained neural nets. This allows signal types to be recognized with a very high degree of accuracy even in low Signal to Noise Ratio (SNR) conditions.

Detection of anomalous signals which indicate threat or interference is another key application which lends itself to a machine learning–based solution. Convolutional neural nets can be trained to distinguish ‘normal’ signals from anomalous signals possibly indicating a threat or unwanted interference. By training the net for a given application, it can be made to learn which signal types and anomalies are important and which are low priority.

Over the course of the webinar, Alistair Massarella will take you through the technical details of these applications and further explore the huge benefits machine learning is set to bring to the EW field.

After you register for the webinar, you will be emailed a confirmation with the link to the webinar, along with instructions on how to connect.

  • To ensure your computer system has access to Adobe Connect, please test your system HERE.  (PLEASE NOTE:  Only steps 1-3 of this test are needed to attend the event.  Step 4 is for event hosts/presenters only.)

You can also access the webinar via free mobile apps available on iOS, Android, and Blackberry devices.

For questions, please contact Brock Sheets.

The entire presentation and Q&A will be recorded for viewing approximately 24 hours after the event. You can find the link to the recording in our AOC Virtual Series Archive.  (separate registration required to view the recording)

*Additional sponsorship opportunities are available. Click here for details.

Webinar Filter

AOC virtual series

Your schedule won't let you attend live??
Don't worry. The entire presentation and Q&A will be recorded for viewing approximately 24 hours after the event. You can find the link to the recording in our AOC Virtual Series Archive.  The AOC offers all past webinars for free to members. A password is required to view archived webinars. Members, click here to get your password and start watching right away. Not a member? Click here to sign up, and start viewing the webinars in minutes!

PLEASE NOTE: By registering for this event, the details of your profile may be used by the Association of Old Crows (AOC), the presenter, or the sponsor(s) to contact you by email.