Abstract: An adaptive threshold approach is applied to detect true touch signals and filter out increased noise signals. More specifically, statistics regarding the signals from a touch screen are used to create a touch signal threshold that changes with the statistics of the touch signals. Accordingly, the threshold can automatically move higher in high noise situations and lower in low noise situations. So configured, fewer noise signals are erroneously interpreted as touches for the device associated with the touch screen.

Abstract: An adaptive threshold approach is applied to detect true touch signals and filter out increased noise signals. More specifically, statistics regarding the signals from a touch screen are used to create a touch signal threshold that changes with the statistics of the touch signals. Accordingly, the threshold can automatically move higher in high noise situations and lower in low noise situations. So configured, fewer noise signals are erroneously interpreted as touches for the device associated with the touch screen.

Abstract: A method of dominant speech extraction is provided that includes acquiring a primary audio signal from a microphone and at least one additional audio signal from at least one additional microphone, wherein the acquired audio signals include speech and noise, decomposing each acquired audio signal into a low frequency sub-band signal and a high frequency sub-band signal, applying speech suppression beamforming to the low frequency sub-band signals to generate a reference channel having an estimate of noise in the low frequency sub-band signals, applying noise cancellation to the low frequency sub-band signal of the primary audio signal using the reference channel to generate a first signal having a low frequency estimate of the speech, applying noise suppression beamforming to the high frequency sub-band signals to generate a second signal having a high frequency estimate of the speech, and combining the first and second signals to generate a full-band audio signal.

Abstract: Touch screen controllers and methods are presented for removing charger noise and other high frequency noise from touch screens in the presence of aliasing in which a digital low pass filter rejects the high frequency noise, a noise tracker determines whether noise is being aliased into the low pass filter pass band, and a noise shaper artificially induces or modifies aliasing in the system by adjusting an analog-to-digital converter sampling frequency and/or a panel scan frequency to try to move the aliased noise outside the low pass filter pass band.

Abstract: Touch screen controllers and methods are presented for removing charger noise and other high frequency noise from touch screens in the presence of aliasing in which a digital low pass filter rejects the high frequency noise, a noise tracker determines whether noise is being aliased into the low pass filter pass band, and a noise shaper artificially induces or modifies aliasing in the system by adjusting an analog-to-digital converter sampling frequency and/or a panel scan frequency to try to move the aliased noise outside the low pass filter pass band.

Abstract: A method of dominant speech extraction is provided that includes acquiring a primary audio signal from a microphone and at least one additional audio signal from at least one additional microphone, wherein the acquired audio signals include speech and noise, decomposing each acquired audio signal into a low frequency sub-band signal and a high frequency sub-band signal, applying speech suppression beamforming to the low frequency sub-band signals to generate a reference channel having an estimate of noise in the low frequency sub-band signals, applying noise cancellation to the low frequency sub-band signal of the primary audio signal using the reference channel to generate a first signal having a low frequency estimate of the speech, applying noise suppression beamforming to the high frequency sub-band signals to generate a second signal having a high frequency estimate of the speech, and combining the first and second signals to generate a full-band audio signal.

Abstract: A first signal is received that represents speech and the noise. The noise includes directional noise and diffused noise. A second signal is received that represents the noise and leakage of the speech. In response to the first and second signals: a first channel is generated that represents the speech and the diffused noise while attenuating most of the directional noise from the first signal; and a second channel is generated that represents the noise while attenuating most of the speech from the second signal. In response to the first and second channels, an output channel is generated that represents the speech while attenuating most of the noise from the first channel.

Abstract: A method and apparatus for cross-talk resistant adaptive noise cancellation.

Abstract: A method and apparatus for joint noise and echo cancellation of a two microphone system subject to cross-talk. The method includes estimating the reference output by removing the cross-talk and the estimated echo from the reference channel, when an echo is detected in the reference echo signal, adapting filters H13 and H23 by NLMS, when the estimated primary output includes speech, adapting filters H12 and H21 by de-correlation, when neither echo nor speech is detected, adapting filter H12 is adapted by NLMS, obtaining the primary output and the reference output by post-filtering of the estimated primary output and the estimated reference output, respectively, and utilizing the primary output and the reference output for canceling the echo and noise of a two microphone system subject to cross-talk.

Abstract: A method and apparatus for cross-talk resistant adaptive noise cancellation.