Abstract: A local priority-based scanning scheme that focuses scanning to areas of a display panel whose measured characteristics are under continuous change (e.g., aging or relaxation). The algorithm identifies areas or regions needing compensation, using a current measurement from a single pixel in an area as a candidate to determine whether the rest of the region needs further compensation. The algorithm thus detects newly changed areas quickly, focusing time-consuming measurements on those areas that need high attention. Optionally, neighboring pixels sharing the same state (e.g., aging or overcompensated) as the measured pixel can be adjusted automatically given the likelihood that the neighboring pixels will also require compensation if the measured pixel needs compensation.

Abstract: A local priority-based scanning scheme that focuses scanning to areas of a display panel whose measured characteristics are under continuous change (e.g., aging or relaxation). The algorithm identifies areas or regions needing compensation, using a current measurement from a single pixel in an area as a candidate to determine whether the rest of the region needs further compensation. The algorithm thus detects newly changed areas quickly, focusing time-consuming measurements on those areas that need high attention. Optionally, neighboring pixels sharing the same state (e.g., aging or overcompensated) as the measured pixel can be adjusted automatically given the likelihood that the neighboring pixels will also require compensation if the measured pixel needs compensation.

Abstract: A local priority-based scanning scheme that focuses scanning to areas of a display panel whose measured characteristics are under continuous change (e.g., aging or relaxation). The algorithm identifies areas or regions needing compensation, using a current measurement from a single pixel in an area as a candidate to determine whether the rest of the region needs further compensation. The algorithm thus detects newly changed areas quickly, focusing time-consuming measurements on those areas that need high attention. Optionally, neighboring pixels sharing the same state (e.g., aging or overcompensated) as the measured pixel can be adjusted automatically given the likelihood that the neighboring pixels will also require compensation if the measured pixel needs compensation.

Abstract: A local priority-based scanning scheme that focuses scanning to areas of a display panel whose measured characteristics are under continuous change (e.g., aging or relaxation). The algorithm identifies areas or regions needing compensation, using a current measurement from a single pixel in an area as a candidate to determine whether the rest of the region needs further compensation. The algorithm thus detects newly changed areas quickly, focusing time-consuming measurements on those areas that need high attention. Optionally, neighboring pixels sharing the same state (e.g., aging or overcompensated) as the measured pixel can be adjusted automatically given the likelihood that the neighboring pixels will also require compensation if the measured pixel needs compensation.

Abstract: A local priority-based scanning scheme that focuses scanning to areas of a display panel whose measured characteristics are under continuous change (e.g., aging or relaxation). The algorithm identifies areas or regions needing compensation, using a current measurement from a single pixel in an area as a candidate to determine whether the rest of the region needs further compensation. The algorithm thus detects newly changed areas quickly, focusing time-consuming measurements on those areas that need high attention. Optionally, neighboring pixels sharing the same state (e.g., aging or overcompensated) as the measured pixel can be adjusted automatically given the likelihood that the neighboring pixels will also require compensation if the measured pixel needs compensation.

Abstract: A local priority-based scanning scheme that focuses scanning to areas of a display panel whose measured characteristics are under continuous change (e.g., aging or relaxation). The algorithm identifies areas or regions needing compensation, using a current measurement from a single pixel in an area as a candidate to determine whether the rest of the region needs further compensation. The algorithm thus detects newly changed areas quickly, focusing time-consuming measurements on those areas that need high attention. Optionally, neighboring pixels sharing the same state (e.g., aging or overcompensated) as the measured pixel can be adjusted automatically given the likelihood that the neighboring pixels will also require compensation if the measured pixel needs compensation.

Abstract: A local priority-based scanning scheme that focuses scanning to areas of a display panel whose measured characteristics are under continuous change (e.g., aging or relaxation). The algorithm identifies areas or regions needing compensation, using a current measurement from a single pixel in an area as a candidate to determine whether the rest of the region needs further compensation. The algorithm thus detects newly changed areas quickly, focusing time-consuming measurements on those areas that need high attention. Optionally, neighboring pixels sharing the same state (e.g., aging or overcompensated) as the measured pixel can be adjusted automatically given the likelihood that the neighboring pixels will also require compensation if the measured pixel needs compensation.

Abstract: A method and system for predicting channel fading, particularly in a mobile wireless environment, that is accurate for long-range predictions. The method comprises estimating a model parameters based on a current channel estimate, and recursively adapting the model parameters to predict future channel fading coefficients until a predetermined re-acquisition condition is satisfied. Once the re-acquisition condition has been satisfied, the model parameters are again estimated based on a current channel estimate. The acquired model parameters are adaptively updated and used in a Kalman filter.

Abstract: A local priority-based scanning scheme that focuses scanning to areas of a display panel whose measured characteristics are under continuous change (e.g., aging or relaxation). The algorithm identifies areas or regions needing compensation, using a current measurement from a single pixel in an area as a candidate to determine whether the rest of the region needs further compensation. The algorithm thus detects newly changed areas quickly, focusing time-consuming measurements on those areas that need high attention. Optionally, neighboring pixels sharing the same state (e.g., aging or overcompensated) as the measured pixel can be adjusted automatically given the likelihood that the neighboring pixels will also require compensation if the measured pixel needs compensation.

Abstract: A method and system for predicting channel fading, particularly in a mobile wireless environment, that is accurate for long-range predictions. The method comprises estimating a model parameters based on a current channel estimate, and recursively adapting the model parameters to predict future channel fading coefficients until a predetermined re-acquisition condition is satisfied. Once the re-acquisition condition has been satisfied, the model parameters are again estimated based on a current channel estimate. The acquired model parameters are adaptively updated and used in a Kalman filter.

Abstract: System and method for blind echo cancellation in a received terahertz signal in a pulsed terahertz system for imaging or spectroscopy. Blind signal processing methods estimate the impulse response of the reflection mechanism and do not require a reference measurement to be taken. The reference signal may be recovered using a successive approach wherein the reference is first estimated using cross-correlation with the received signal and the received signal is represented as a function of the reference signal. For each successive echo, the calculated echo may be subtracted from the received signal and then the estimate of the reference signal is refined. Using an analytical approach, the parameters of a transfer function modeling the reflection mechanism may be estimated by optimizing a cost function.

Abstract: System and method for blind echo cancellation in a received terahertz signal in a pulsed terahertz system for imaging or spectroscopy. Blind signal processing methods estimate the impulse response of the reflection mechanism and do not require a reference measurement to be taken. The reference signal may be recovered using a successive approach wherein the reference is first estimated using cross-correlation with the received signal and the received signal is represented as a function of the reference signal. For each successive echo, the calculated echo may be subtracted from the received signal and then the estimate of the reference signal is refined. Using an analytical approach, the parameters of a transfer function modeling the reflection mechanism may be estimated by optimizing a cost function.

Abstract: A system, method and an apparatus for terahertz (THz) imaging based on compressed sensing using a unified sensing mask are provided herein. The system may include a THz radiation transmitter, a window, a unified mask, a THz radiation focusing lens, a THz radiation detector and a processor to generate an image using compressed sensing. The unified mask includes a series of individual masks for filtering radiation directed at the individual masks. Each of the individual masks defines a binary two-dimensional matrix of cells that are either a radiation blocking cell or a radiation passing cell. The unified mask has a first length in a first direction. The window has a terahertz radiation blocking border that defines a terahertz radiation passing opening.

Abstract: A method and system for predicting channel fading, particularly in a mobile wireless environment, that is accurate for long-range predictions. The method comprises estimating a model parameters based on a current channel estimate, and recursively adapting the model parameters to predict future channel fading coefficients until a predetermined re-acquisition condition is satisfied. Once the re-acquisition condition has been satisfied, the model parameters are again estimated based on a current channel estimate. The acquired model parameters are adaptively updated and used in a Kalman filter.