Abstract: An identity recognition system based on compressed signals and a method thereof are provided. When a sensing end is in an identification mode, it continuously measures a physiological identification signal of a user having at least one first predetermined length of time, and performs a compression process on the physiological identification signal having at least one first predetermined length of time to generate a first compressed signal. An identification end receives the first compressed signal, obtains first identification information of the first compressed signal in a discrimination subspace according to a principal eigenvector, and recognizes the first identification signal according to a classification model from a learning end to determine that the user is one of multiple subjects.

Abstract: An authorization system based on biometric identification and a method thereof are provided. An incomplete physiological signal of a subject is obtained. Next, the incomplete physiological signal is analyzed according to a machine learning model to identify an identity corresponding to the subject, and then output identity information. Then, whether the authorization is obtained based on the identity information is determined. When the authorization is obtained, the authorization content is provided. Therefore, in the case where the physiological signal is an incomplete signal, it is possible to perform identity recognition based on the machine learning model, and then to determine whether to provide the corresponding authorization content, so as to achieve the technical efficacy of recognition stability.

Abstract: An identity recognition system based on compressed signals and a method thereof are provided. When a sensing end is in an identification mode, it continuously measures a physiological identification signal of a user having at least one first predetermined length of time, and performs a compression process on the physiological identification signal having at least one first predetermined length of time to generate a first compressed signal. An identification end receives the first compressed signal, obtains first identification information of the first compressed signal in a discrimination subspace according to a principal eigenvector, and recognizes the first identification signal according to a classification model from a learning end to determine that the user is one of multiple subjects.

Abstract: A bloom filter and an implementation method thereof are provided. The implementation method has a ternary rule encoded as a rule binary codeword according to a predetermined encoding rule; has a packet encoded as at least one packet binary codeword according to the predetermined encoding rule; and comparing the rule binary codeword and the at least one packet binary codeword to decide a following processing of the packet. The predetermined encoding rule includes: tagging 0 or 1 into most significant bit (MSB) of the output binary codeword based on mask length of the input codeword; placing the prefix of the input codeword right after MSB of the output binary codeword; and tagging a string to last bits of the output binary codeword based on the mask length, and the bit number of the string equals to the mask length.

Abstract: A measurement matrix generating system based on scrambling and a method thereof are disclosed. A plurality of independent identically distributed (i.i.d) elements is pre-stored in a circulant matrix register array, selections are made among the elements so as to perform an algebraic operation on the selected elements, and a measurement matrix with high availability is generated according to results of the operations, so as to achieve the technical effect of improving the availability of the measurement matrix in compressive sensing.

Abstract: A system for acquiring channel knowledge and a method thereof are provided. At least one transmitter generates multiple directional beams in different directions, next modulates the directional beams in the different directions with at least one spreading sequence, so as to enlarge the beam range of each directional beam in the different directions and use the modulated directional beams as training-specific beams in the different directions, and sweeps the multiple training-specific beams in the different directions by using a plurality of antennas, so that at least one receiver measures at least one training-specific beam, and determines the channel knowledge according to the measurement result and beam-related information associated with the at least one training-specific beam, so as to achieve a technical effect of reducing training overhead.

Abstract: The present disclosure illustrates a ternary content addressable memory (TCAM) device for software defined networking and method thereof. In the TCAM device, M bits of each forwarding rule is stored as a first part into a NAND-Type TCAM, and N bits of the same forwarding rule is stored as a second part into a NOR-Type TCAM. M bits of searching data is compared with the first part to generate a first matching result, N bits of the searching data is compared with the second part to generate a second matching result when the first matching result indicates match, and comparing process for the second part is disabled when the first matching result indicates mismatch. The mechanism is help to improve flexibility of the TCAM in words length and to reduce power consumption.

Abstract: A system for acquiring channel knowledge and a method thereof are provided. At least one transmitter generates multiple directional beams in different directions, next modulates the directional beams in the different directions by means of at least one spreading sequence, so as to enlarge the beam range of each directional beam in the different directions and use the modulated directional beams as training-specific beams in the different directions, and sweeps the training-specific beams in the different directions by means of a plurality of antennas, so that at least one receiver measures at least one training-specific beam, and determines the channel knowledge according to the measurement result and beam-related information associated with the at least one training-specific beam, so as to achieve a technical effect of reducing training overhead.

Abstract: A measurement matrix generating system based on scrambling and a method thereof are disclosed. A plurality of independent identically distributed (i.i.d) elements is pre-stored in a circulant matrix register array, selections are made among the elements so as to perform an algebraic operation on the selected elements, and a measurement matrix with high availability is generated according to results of the operations, so as to achieve the technical effect of improving the availability of the measurement matrix in compressive sensing.

Abstract: Disclosed are a compressive sensing system based on a personalized basis and a method thereof; first a sensing end senses an original signal and transmits the original signal to a reconstruction end; the reconstruction end generates a personalized basis by means of a dictionary learning method; next, the sensing end is made to sample the original signal according to a sampling matrix to generate a compressed signal and transmit the compressed signal to the reconstruction end, so that the reconstruction end executes a compressive sensing reconstruction algorithm according to the personalized basis and the compressed signal to recover the compressed signal into the original signal, thereby achieving an effect of improving signal recovering quality and a compression ratio.

Abstract: Disclosed are a compressive sensing system based on a personalized basis and a method thereof; first a sensing end senses an original signal and transmits the original signal to a reconstruction end; the reconstruction end generates a personalized basis by means of a dictionary learning method; next, the sensing end is made to sample the original signal according to a sampling matrix to generate a compressed signal and transmit the compressed signal to the reconstruction end, so that the reconstruction end executes a compressive sensing reconstruction algorithm according to the personalized basis and the compressed signal to recover the compressed signal into the original signal, thereby achieving an effect of improving signal recovering quality and a compression ratio.

Abstract: A multi-channel sensing system and operating method thereof are disclosed. The multi-channel sensing system includes a transceiver, emitting electrodes, and a receiving electrode. The transceiver includes a spreading code generator and a modulator. The spreading code generator generates a non-orthogonal spreading code through an invertible matrix and then the modulator modulates a data signal to spreading signals according to the non-orthogonal spreading code. The emitting electrodes, corresponding to sensing channels respectively, emit the spreading signals at the same time to pass through corresponding sensing channels respectively, and the spreading signals are converted into coupled signals by capacitive coupling. The receiving electrode receives the coupled signals and generates a received signal according to the coupled signals.

Abstract: A signal decomposition system with low-latency empirical mode decomposition and the method of the same decompose an original signal using iterative computations with different directions of data streams. The directions of data stream in computations of odd or even iterations are adjusted for reducing the number of data stream direction reversals. As a result, computing data can be shared and computing time can be saved. The mechanism helps improve the efficiency of signal decompositions.

Abstract: A temperature prediction system and method thereof use sensors to sense the temperature at a plurality of times, thereby calculating an actual temperature difference between the current time and the previous time. According to the result of actual temperature difference, an adaptive filter is used to predict a predicted temperature difference at a future time and to add the temperature of the current time and the predicted temperature difference to render a predicted temperature. By calculating the difference between the temperature at the next time and the predicted temperature at the next time, the filter parameter of the adaptive filter is adjusted. This mechanism helps improving the accuracy in temperature predictions.

Abstract: A multi-channel sensing system and operating method thereof are disclosed. The multi-channel sensing system includes a transceiver, emitting electrodes, and a receiving electrode. The transceiver includes a spreading code generator and a modulator. The spreading code generator generates a non-orthogonal spreading code through an invertible matrix and then the modulator modulates a data signal to spreading signals according to the non-orthogonal spreading code. The emitting electrodes, corresponding to sensing channels respectively, emit the spreading signals at the same time to pass through corresponding sensing channels respectively, and the spreading signals are converted into coupled signals by capacitive coupling. The receiving electrode receives the coupled signals and generates a received signal according to the coupled signals.

Abstract: A method for performing channel shortening equalization with frequency notch mitigation is provided, where the method is applied to an electronic device. The method includes: obtaining channel response information from channel estimation to determine a relaxed channel convolution matrix corresponding to the channel response information, with the relaxed channel convolution matrix being a partial matrix of a channel convolution matrix corresponding to the channel response information, wherein the relaxed channel convolution matrix is obtained from omitting a portion of matrix elements of the channel convolution matrix; and based upon the relaxed channel convolution matrix, jointly performing time domain channel shortening control and frequency domain flatness control over the TEQ to perform channel shortening equalization with frequency notch mitigation by utilizing the TEQ. In particular, the portion of matrix elements includes a plurality of rows of matrix elements within the channel convolution matrix.

Abstract: A low complexity motion compensating beamforming system utilizes a probe array to fire for beamforming by synthetic apertures. The beamforming range of each firing is a region of interest (ROI), and the common area of adjacent ROI's forms the common ROI. The central image beam of the common ROI is used to generate image beam vectors, in order to analyze the cross-correlation for the corresponding low resolution images (LRI's). The analysis result is used to compute an offset for sequentially compensating and combining the LRI's to form a high resolution image (HRI). The mechanism helps improve the quality of ultrasonic beamforming and the frame rate.

Abstract: A method for performing channel shortening equalization with frequency notch mitigation is provided, where the method is applied to an electronic device. The method includes: obtaining channel response information from channel estimation to determine a relaxed channel convolution matrix corresponding to the channel response information, with the relaxed channel convolution matrix being a partial matrix of a channel convolution matrix corresponding to the channel response information, wherein the relaxed channel convolution matrix is obtained from omitting a portion of matrix elements of the channel convolution matrix; and based upon the relaxed channel convolution matrix, jointly performing time domain channel shortening control and frequency domain flatness control over the TEQ to perform channel shortening equalization with frequency notch mitigation by utilizing the TEQ. In particular, the portion of matrix elements includes a plurality of rows of matrix elements within the channel convolution matrix.

Abstract: A method for performing a singular value decomposition (SVD) upon a matrix. The method includes the steps of: (a) simplifying the matrix to derive a simplified matrix; (b) performing an iterative matrix multiplication upon the simplified matrix to generate an iterated matrix; (c) extracting a vector of the iterated matrix according to an iteration number of the iterative matrix multiplication; (d) de-correlating the simplified matrix from the vector to update the simplified matrix; (e) repeating steps (b), (c), and (d) until a predetermined number of vectors have been derived; and (f) storing a first unitary matrix determined according to the predetermined number of vectors in the singular value decomposition.

Abstract: A programmable LDPC (Low-Density Parity-Check) code decoder and decoding method thereof is disclosed. By combining at least one programmable switch and at least one memory unit to decode any quasi-cyclic-based parity check matrix, one can set the switch state of the programmable switch to dynamically adjust the size of the decoding matrix and determine the locations of 1's and 0's in the decoding matrix. The mechanism helps improving the usability and flexibility of the decoding matrix.