Cirrus Logic. has filed a patent for an adaptive noise-canceling system that generates an anti-noise signal using a filter controlled by coefficients. The system includes microphones for measuring ambient noise at different locations and a controller that selects coefficients based on phase differences between noise signals. GlobalData’s report on Cirrus Logic gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Cirrus Logic, Voice biometrics was a key innovation area identified from patents. Cirrus Logic's grant share as of January 2024 was 64%. Grant share is based on the ratio of number of grants to total number of patents.
Adaptive noise-canceling system for generating anti-noise signal
A recently filed patent (Publication Number: US20240038211A1) describes an adaptive noise-canceling system designed to generate an anti-noise signal. The system includes a filter with a response controlled by a set of coefficients selected from a collection of coefficient sets, an acoustic output transducer, first and second microphones for measuring ambient noise at different locations, an analysis subsystem, and a controller that selects the coefficients based on the phase difference between the noise measurement signals from the two microphones. The controller also adjusts an adjustable gain stage to achieve an operational gain state and selects an operating set of coefficients for the filter based on phase differences across multiple frequency bins.
Furthermore, the patent also details a method for canceling the effects of ambient noise using the adaptive noise-canceling system. The method involves sensing ambient noise with two acoustic sensors, generating an anti-noise signal with a filter controlled by a set of coefficients, providing the anti-noise signal to an output transducer, analyzing noise measurement signals to determine phase differences, and controlling the filter response based on these phase differences. The method also includes selecting initial coefficients, adjusting an adjustable gain stage, evaluating stability and angle of phase differences, selecting coefficients for multiple frequency bins, and maintaining phase differences within a predetermined bound. Additionally, the method involves classifying coefficients, determining the presence of program audio, and selecting coefficients accordingly, as well as transforming responses to a lower-dimensional subspace for coefficient selection. The filter in this method can be either an infinite-impulse response (IIR) filter or a finite-impulse response (FIR) filter.
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