Abstract: A display device includes a plurality of light sources, a plurality of display driver integrated circuits (DDICs), and a light source driver. The light sources are configured to illuminate a display panel comprising a plurality of regions. Each DDIC is configured to generate backlighting data for a respective region of the plurality of regions. The backlighting data is indicative of luminance levels of respective light sources, of the plurality of light sources, which correspond to the respective region of the plurality of regions. Each DDIC is further configured to store ordering information indicative of an order for outputting the backlighting data, and output the backlighting data for the respective region based on the ordering information and a backlighting data synchronization signal. The light source driver is configured to drive the plurality of light sources based on the backlighting data for the plurality of regions output from the plurality of DDICs.

Abstract: A method performed by a docking station operable in a plurality of modes is disclosed. The method may include obtaining first data via a first interface of the docking station and second data via a second interface of the docking station, responsive to operating in a first mode of the plurality of modes. The first interface may be configured to couple the docking station to a computing device, and the second interface may be configured to communicate with a network. The method may also include obtaining third data via the second interface of the docking station, in lieu of the first interface, responsive to operating in a second mode of the plurality of modes. The method may further include selectively outputting the first data and the second data, or the third data, to a display based on whether the docking station operates in the first mode or the second mode.

Abstract: This disclosure provides methods, devices, and systems for exposure control for digital images. The present implementations more specifically relate to dynamic region-of-interest (ROI) based auto-exposure control. In some implementations, an imaging system may a first image in a series of images using a first exposure setting. The imaging system may detect one or more regions of interest (ROI) in the first image. The imaging system may determine a first brightness value associated with a first ROI in the first image. The imaging system may determine a second exposure setting based on the first brightness value. The imaging system may capture a second image in the series of images, subsequent to the first image, using the second exposure setting.

Abstract: Methods and systems for close detection are provided. An input device has an opened state and a closed state. The input device includes a first portion comprising a touch sensor having a sensing area. The touch sensor includes a plurality of transmitter electrodes and a plurality of receiver electrodes. The input device also has a second portion comprising a plurality of features. A sensor circuit is configured to drive the plurality of transmitter electrodes with sensing signals and receive resulting signals from the plurality of receiver electrodes. A processing system is configured to generate an acquired image from at least a portion of the sensing area; compare the acquired image to a reference image, wherein the reference image includes data corresponding to the plurality of features; and determine whether the input device is in the closed state based on the comparison of the acquired image to the reference image.

Abstract: This disclosure provides methods, devices, and systems for active noise control (ANC). The present implementations more specifically relate to filter adaptation techniques for recursively training an infinite impulse response (IIR) filter to convert a reference audio signal to an anti-noise signal. In some aspects, an ANC system may record, via a feedforward microphone, a reference audio signal representing external noise, and may further record, via a feedback microphone, an error signal representing residual noise resulting from passive attenuation of the external noise via a primary path between the microphones. The ANC system may further estimate an IIR filter that converts the reference audio signal to the error signal based on a secondary path. In some implementations, the ANC system may recursively update the IIR filter coefficients based, at least in part, on the coefficients associated with previous frames of the reference audio signal and the error signal.

Abstract: A method for performing a scanning process using adaptive scanning, comprising: driving, by a processing system of an input device, one or more of a first set of electrodes to generate first sensing signals that are detectable by a second set of electrodes; obtaining first resulting signals associated with the first sensing signals via the second set of electrodes; determining, based on the first resulting signals, a first subset of the second set of electrodes that detected an input object on a display device; driving one or more of the first subset of the second set of electrodes that detected the input object to generate second sensing signals that are detectable by the first set of electrodes; and obtaining second resulting signals associated with the second sensing signals via the first set of electrodes.

Abstract: This disclosure provides methods, devices, and systems for audio signal processing. The present implementations more specifically relate to low-latency speech enhancement. In some aspects, a speech enhancement system may receive a number (B) of frames of a signal, where each of the B frames include a number (N) of time-domain samples. The speech enhancement system may transform the B*N time-domain samples into B*N first frequency-domain samples based on an N-point fast Fourier transform (FFT), and may further transform the B*N first frequency-domain samples into B*N second frequency-domain samples based on a B-point FFT. The speech enhancement system may determine a probability of speech in the signal based at least in part on the B*N second frequency-domain samples. In some implementations, the speech enhancement system may decimate the B*N second frequency-domain samples by a factor (D), and the probability of speech is determined based on the B*N/D decimated second frequency-domain samples.

Abstract: A method and a system for operating an artificial intelligence (AI) assistant. In some implementations, a method may include receiving a user input, the user input including a user question; generating a first vector representing the user question; matching the first vector to a second vector representing a question stored in a database of questions and answers at the computing device, the database of questions and answers including a plurality of questions extracted from a knowledge base associated with the computing device and respective answers associated with the plurality of questions; and selectively escalating the user question for processing by a machine learning model.

Abstract: A sensing device and method for driving segmented electrodes is provided. The sensing device includes a sensing area having a first sensing region and a second sensing region. The sensing device also includes a plurality of receiver electrodes comprising a first set of receiver electrodes disposed in the first sensing region and a second set of receiver electrodes disposed in the second sensing region and a plurality of segmented transmitter electrodes. Each segmented transmitter electrode comprises a first transmitter electrode and a second transmitter electrode. The first transmitter electrode is isolated from the second transmitter electrode such that the first transmitter electrode is separately controllable from the second transmitter electrode. The first transmitter electrode is disposed in the first sensing region and the second transmitter electrode is disposed in the second sensing region.

Abstract: A memory device having a plurality of groups of words is provided. Each group of the plurality of groups of words are stored in a contiguous section of a memory and each group of the plurality of groups of words includes a plurality of words. The plurality of words each have a plurality of elements with a same set of index values for a first dimension of a tensor and a same set of index vales for a second dimension of a tensor. The plurality of words have a different index value for a third dimension of the tensor.

Abstract: This disclosure provides methods, devices, and systems for video coding. The present implementations more specifically relate to autoencoders that support infer-frame coding in the latent domain. A video encoder may convert a frame of video from the pixel domain to the latent domain based on a machine learning model. For example, the machine learning model may be trained to transform the video frame into a tensor of latent attributes. In some aspects, the video encoder may combine the resulting tensor with a tensor of latent attributes associated with a previously-encoded video frame and transform the resulting tensor into a vector that includes latent attributes from both the current video frame and the previous video frame based on an inter-coding transform. More specifically, the inter-coding transform may reduce a dimensionality of the combined tensor so that the resulting vector is smaller or more compressible than the original tensor of latent attributes.

Abstract: A method for performing a reconstructed temperature stable profile sensing scheme is provided. The method comprises: based on driving a first subset of a plurality of electrodes, obtaining first resulting signals from a second subset of the plurality of electrodes; based on driving both the first subset and the second subset of the plurality of electrodes, obtaining second resulting signals from the second subset of the plurality of electrodes; determining a reconstructed temperature stable profile based on a mutual capacitance sensing profile associated with the first resulting signals, an absolute capacitance sensing (ABS) profile associated with the second resulting signals, and a reconstructed temperature stable parameter; and performing object detection based on the reconstructed temperature stable profile.

Abstract: This disclosure provides methods, devices, and systems for image scaling. The present implementations more specifically relate to downscaling techniques that preserve a subset of pixel values in a digital image so that all reconstructed pixel values in the upscaled image can be interpolated based on two or more preserved pixel values. In some aspects, an image downscaler may partition a digital image into a number of image tiles based on a base tile size and one or more scaling factors associated with a downscaling operation used to downscale each image tile. The base tile size indicates the dimensions of the downscaled tiles. The one or more scaling factors indicate distances between the pixel values preserved as a result of one or more iterations, respectively, of the downscaling operation, where each iteration preserves a smaller subset of the pixel values from the original image (as a lower resolution tile).

Abstract: A system for classifying touch data is provided. The system comprises: a plurality of sensing elements; and a processing system. The processing system is configured to: receive touch data from a current user via the plurality of sensing elements; determine a first set of classifier parameters corresponding to a current user based on usage data, wherein the usage data comprises the touch data from the current user, and apply the first set of classifier parameters to classify subsequent touch data.

Abstract: This disclosure provides methods, devices, and systems for achieving connected vehicle functionality. The present implementations more specifically relate to installation-free Internet of things (IoT) sensors for automobiles. In some aspects, an IoT device may include a housing having a power connector configured to interface with an auxiliary power outlet of an automobile and also may include one or more sensors, disposed within the housing, configured to detect changes to a surrounding environment. Example suitable changes may include sounds from the surrounding environment. In some implementations, the IoT device may further include a network interface disposed within the housing and configured to transmit information associated with the detected changes to a wireless communication device. Example suitable information may include a notification about important changes in the automobile's environment.

Abstract: This disclosure provides methods, devices, and systems for wireless communications. The present implementations more specifically relate to trigger frame designs that support early validation of trigger frames. In some aspects, an AP may transmit a trigger frame soliciting a trigger-based (TB) physical layer convergence protocol (PLCP) protocol data unit (PPDU) from one or more wireless stations (STAs), where the trigger frame includes one or more user information fields, an early frame check sequence (eFCS) following the user information fields, a series of padding bits following the eFCS, and a frame check sequence (FCS) following the series of padding bits. Each STA associated with the AP may receive and validate a first portion of the trigger frame based on the eFCS. Any non-solicited STAs that receive the trigger frame may enter a low power mode in response to validating the first portion of the trigger frame, without receiving the padding bits.

Abstract: A method of suppressing noise may include receiving a sequence of audio frames representing a multi-channel audio signal. The method may include determining a likelihood of speech in a first audio frame of the sequence of audio frames based on a Gaussian mixture model. Further, the method may include generating a first audio signal based on the likelihood of speech in the first audio frame and a second audio signal representing a first speech component of a second audio frame. The second audio frame follows the first audio frame in the sequence of audio frames. The method may also include determining, using a neural network model, a likelihood of speech in the second audio frame based on the first audio signal, and filtering a noise component of the second audio frame based at least in part on the likelihood of speech in the second audio frame.

Abstract: This disclosure provides methods, devices, and systems for audio signal processing. The present implementations more specifically relate to speech enhancement techniques that combine statistical signal processing with neural network inferencing. In some aspects, a speech enhancement system may include a linear filter, a deep neural network (DNN), and a nonlinear post-filter. The linear filter and the nonlinear post-filter are configured to suppress noise in audio signals using statistical signal processing techniques. More specifically, the linear filter denoises an input audio signal based on a temporal correlation between successive frames of the audio signal. The DNN infers a speech signal and a noise signal (representing a speech component and a noise component, respectively, of the audio signal) based on the denoised audio signal.

Abstract: A display driver includes a plurality of gamma bus lines and a drive leg configured to receive pixel data. The drive leg includes a decoder having first and second outputs, a source amplifier having a set of inputs, and a source interpolation selector. The decoder electrically connects, based on the pixel data, the first output to a first one of the gamma bus lines and the second output to a second one of the gamma bus lines. The source amplifier provides a data voltage to a display panel based on a set of input voltages at the set of inputs. The source interpolation selector provides, based on the pixel data, electrical connections between the first and second outputs of the decoder and the set of inputs of the source amplifier, and electrically connects the first and second outputs of the decoder during a first period of a horizontal sync period.

Abstract: A method for demura calibration is provided. The method includes acquiring a plurality of brightness maps of a plurality of light sources of a two-dimensional backlight system for a plurality of test patterns, each test pattern indicating each of the plurality of light sources to be turned on or off. Each of the plurality of light sources is turned on in only one of the plurality of test patterns. The plurality of brightness maps indicate brightness levels of the plurality of light sources for the plurality of test patterns. The method further includes producing a cumulative brightness map by adding together the plurality of brightness maps. The method further includes generating demura compensation factors for the plurality of light sources based on the cumulative brightness map.