Abstract: An electronic device display may have pixels formed from crystalline semiconductor light-emitting diode dies, organic light-emitting diodes, or other pixel structures. The pixels may be formed on a display panel substrate. A display panel may extend continuously across the display or multiple display panels may be tiled in two dimensions to cover a larger display area. Interconnect substrates may have outwardly facing contacts that are electrically shorted to corresponding inwardly facing contacts such as inwardly facing metal pillars associated with the display panels. The interconnect substrates may be supported by glass layers. Integrated circuits may be embedded in the display panels and/or in the interconnect substrates. A display may have an active area with pixels that includes non-spline pixels in a non-spline display portion located above a straight edge of the display and spline pixel in a spline display portion located above a curved edge of the display.

Abstract: A real-time multi-channel EEG signal processor based on an on-line recursive independent component analysis is provided. A whitening unit generates covariance matrix by computing covariance according to a received sampling signal. A covariance matrix generates a whitening matrix by a computation of an inverse square root matrix calculation unit. An ORICA calculation unit computes the sampling signal and the whitening matrix to obtain a post-whitening sampling signal. The post-whitening sampling signal and an unmixing matrix implement an independent component analysis computation to obtain an independent component data. An ORICA training unit implements training of the unmixing matrix according to the independent component data to generate a new unmixing matrix. The ORICA calculation unit may use the new unmixing matrix to implement an independent component analysis computation. Hardware complexity and power consumption can be reduced by sharing registers and arithmetic calculation units.

Abstract: A real-time multi-channel automatic eye blink artifact eliminator includes a receiving unit for receiving independent component data; a temporary storage unit for saving pieces of the independent component data to form a data segment; a detection unit for detecting an eye blink artifact in the data segment through a sample entropy algorithm to generate a sample entropy value corresponding to the data segment; and a processing unit for determining whether the data segment contains the eye blink artifact according to the sample entropy value to generate an output result, eliminating the eye blink artifact according to the output result and outputting processed independent component data. The receiving unit continuously receives a next piece of the independent component data and the temporary storage unit discards the oldest one and adds a new one to form a new data segment, thereby continuously performing the eye blink artifact elimination to each data segment.

Abstract: A real-time multi-channel EEG signal processor based on an on-line recursive independent component analysis is provided. A whitening unit generates covariance matrix by computing covariance according to a received sampling signal. A covariance matrix generates a whitening matrix by a computation of an inverse square root matrix calculation unit. An ORICA calculation unit computes the sampling signal and the whitening matrix to obtain a post-whitening sampling signal. The post-whitening sampling signal and an unmixing matrix implement an independent component analysis computation to obtain an independent component data. An ORICA training unit implements training of the unmixing matrix according to the independent component data to generate a new unmixing matrix. The ORICA calculation unit may use the new unmixing matrix to implement an independent component analysis computation. Hardware complexity and power consumption can be reduced by sharing registers and arithmetic calculation units.