Abstract: A semiconductor package including one or more dam structures and the method of forming are provided. A semiconductor package may include an interposer, a semiconductor die bonded to a first side of the interposer, an encapsulant on the first side of the interposer encircling the semiconductor die, a substrate bonded to the a second side of the interposer, an underfill between the interposer and the substrate, and one or more of dam structures on the substrate. The one or more dam structures may be disposed adjacent respective corners of the interposer and may be in direct contact with the underfill. The coefficient of thermal expansion of the one or more of dam structures may be smaller than the coefficient of thermal expansion of the underfill.

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: Data theft prevention technology for a personal electronic device is provided. When an internet-communication address of the personal electronic device is detected by a server through the internet and the server determines that the detected internet-communication address has been listed in a lost list, a processing unit of the personal electronic device operates in accordance with anti-theft software to execute the codes contained in a BIOS memory of the personal electronic device to set a medium password for a user-data storage medium of the personal electronic device and to prohibit the use of the personal electronic device.

Abstract: Data theft prevention technology for a personal electronic device is provided. When an internet-communication address of the personal electronic device is detected by a server through the internet and the server determines that the detected internet-communication address has been listed in a lost list, a processing unit of the personal electronic device operates in accordance with anti-theft software to execute the codes contained in a BIOS memory of the personal electronic device to set a medium password for a user-data storage medium of the personal electronic device and to prohibit the use of the personal electronic device.

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.

Abstract: A real-time signal processing system and method based on multi-channel independent component analysis (ICA). A one-pass recursive ICA processor uses a computation module to perform multi-channel ICA on a set of first data to generate a plurality of second data and third data. A noise removing module uses the computation module to identify noise in the second data and remove the identified noise to generate a plurality of fourth data. A reconstruction module uses the computation module to reconstruct the set of first data based on the fourth data and the third data to generate a plurality of fifth data. The one-pass recursive ICA processor, the noise removing module, the reconstruction module and the computation module are all implemented on a single chip, such that the one-pass recursive ICA processor, the noise removing module and the reconstruction module share the same computation module to save hardware resources.