We’re thrilled by the fantastic turnout at our first IEEE Life Members meeting of 2025! The discussions were insightful, and it was inspiring to see so many attendees eager to volunteer and contribute. Now, we’re gearing up for our second meeting, where we’ll: - Collect contact information - Gather ideas for sharing and preserving industry wisdom - Plan the LMAG Kickoff Meeting for September or October Please join us in person at Joe Decur’s beautiful lakeside home, at 18814 SE 42nd St, Issaquah or join us remotely, Zoom coordinates: Join Zoom Meeting (https://urldefense.com/v3/__https:/washington.zoom.us/j/2366026940?omn=95666517688__;!!K-Hz7m0Vt54!mihGAbqA8Pczn5CbtRpdtYaUH-tyFKYpBTLzfHlOnIlc8L8dpHvCGxsI-Hb2Afz_GAoRQ36OBUKPHqn3Cqtu$) Meeting ID: 236 602 6940 Co-sponsored by: IEEE Seattle Life Member, IEEE Seattle Section Agenda: Monday , August 11, 7pm Planning for future events. 18814 SE 42nd St, , Issaquah, Washington, United States, 98027

Generative Adversarial Networks (GANs) implement Machine Learning (ML) algorithms that can address competitive resource allocation problems, together with detection and mitigation of anomalous behavior. In this talk, the speaker will discuss their use in next-generation (NextG) communications within the context of cognitive networks to address i) spectrum sharing, ii) detecting anomalies, and iii) mitigating security attacks. GANs have the following advantages. First, they can learn and synthesize field data, which can be costly, time-consuming, and non-repeatable. Second, they enable pre-training classifiers by using semisupervised data. Third, they facilitate increased resolution. Fourth, they enable recovering corrupted bits in the spectrum. The talk will provide basics of GANs, a comparative discussion on different kinds of GANs, performance measures for GANs in computer vision and image processing as well as wireless applications, a number of datasets for wireless applications, performance measures for general classifiers, a survey of the literature on GANs for i)–iii) above, some simulation results, and future research directions. In the spectrum sharing problem, connections to cognitive wireless networks are established. Simulation results show that a particular GAN implementation is better than a convolutional autoencoder for an outlier detection problem in spectrum sensing. Co-sponsored by: Vishnu S. Pendyala, SJSU Speaker(s): Dr. Vishnu S. Pendyala, Prof. Ender Ayanoglu Virtual: https://events.vtools.ieee.org/m/493301

Join Us for a Magnificent Sunset Dinner at the Columbia Tower Club Experience breathtaking views from the 76th floor of the Columbia Tower as the sun sets over tranquil Lake Washington, with boats rippling across the water below. Savor exquisite five-star cuisine in an unforgettable setting. We are honored to welcome Dr. Thomas Coughlin, IEEE Past President (2024), as our distinguished guest speaker. Featured Talk: "Where in the World is Tom Coughlin?" Don’t miss this inspiring evening of conversation, connection, and celebration. Speaker(s): Tom Coughlin, Agenda: 6:00 - 6:30 pm Networking 6:30- 7:30 pm Dinner with your fellow chapter members, discuss the chapter plan, or nominate officers. 7:00- 7:30pm Speech, Tom Coughlin, IEEE Past President 2025 " Wheree is Tom Coughlin in the world" 7:30 - 8:30 pm Technical meeting and discuss IEEE New Era AI exciting programs and watch the Sunset. 8:30 pm end Room: 76 floor, Bldg: columbia tower, 701 5th Ave 75th floor, , Seattle , Washington, United States, 98104, Virtual: https://events.vtools.ieee.org/m/494851