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Bryant Sorensen

Bryant Sorensen is Principal DSP Engineer with Eargo, a startup developing 'invisible' completely-in-the-ear hearing aids. He has more than 26 years of experience in audio DSP implementations in firmware, SoCs, and ASIP / programmable DSP core designs. The majority of his career has been spent in hearing aids with Eargo, Knowles, and Starkey Hearing Technologies, with other time at Cirrus Logic and Mythic. He is an expert in low-power implementations that enable hearing aid audio signal processing, in both FW and HW. He holds an MSEE from the University of Tennessee Space Institute, and a B.A. in Computational Mathematics from Utah State University.

Low-Power Algorithmic Approaches in DSP Implementations (2020)

Status: Available Now

Hearing aid signal processing is a challenging task because of the extreme low-power, highly-constrained cycle performance required. The audio signal processing is always on, and requires complex algorithms and computations. A typical hearing aid will have multi-band analysis and synthesis, automatic feedback cancellation, environment detection and action, automatic gain control, and user interface - and AI is arriving as well. In order to reconcile the two disparate requirements (complexity vs. low power & reduced cycles), various approaches are needed to achieve low power while still providing sophisticated calculations. In this talk, I will discuss a sampling of numerical methods, shortcuts, refactorings, and approximations which significantly lower power in DSP algorithms. This will be an overview which I hope sparks thinking to extend the presented concepts to other low-power algorithmic tasks. While the focus is on algorithms and computations, some of these topics will also touch on implications to HW design, HW vs. FW tradeoffs, and ASIP / programmable DSP core design.

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