134 results about "Linear algorithm" patented technology

The invention discloses methods and devices for data encrypting and decrypting and a communication system. The method for data encrypting comprises the following steps: segmenting data into segment data comprising at least two segments; encrypting the segment data in parallel to obtain the ciphertext of the segment data; adopting a linear algorithm to calculate all the segment data in parallel to obtain a message authentication code; and obtaining encrypted data according to the ciphertext and the message authentication code. The method for data decrypting comprises the following steps: segmenting data to be verified to obtain ciphertext segments and a message authentication code; decrypting all segment ciphertext to obtain decipher text and decipher text segments; adopting the linear algorithm to calculate all the decipher text in parallel to obtain a check code; and judging whether the data to be verified is right or not according to the check code and the message authentication code.

The invention discloses a vehicular ad-hoc network data security sharing and storage system based on a blockchain technology. The vehicular ad-hoc network data security sharing and storage system based on the blockchain technology comprises a vehicle, a roadside unit, and a trusted institution. When data shared by the roadside unit, the vehicle performs digital signature on interactive informationby using a bilinear algorithm based on an elliptic curve to ensure the non-repudiation and integrity of the data; the roadside unit packs the collected data into a block, and uses the Byzantine fault-tolerant consensus mechanism to make the data block reach a coherent protocol across the network, thereby improving the fault tolerance of the system and making system more stable; after reaching theconsensus, the block is sorted by a smart contract in the roadside unit and stored in the blockchain, and other consensus nodes save the data synchronously; and the system rewards a corresponding number of data coins to the roadside unit, and then the data coins are assigned to the vehicle contributing the data by the smart contract, so as to keep the entire system active and stable.

The invention provides a neck-worn sensor that is a single, body-worn system that measures the following parameters from an ambulatory patient: heart rate, pulse rate, pulse oximetry, respiratory rate, temperature, thoracic fluid levels, stroke volume, cardiac output, and a parameter sensitive to blood pressure called pulse transit time. From stroke volume, a first algorithm employing a linear model can estimate the patient's pulse pressure. And from pulse pressure and pulse transit time, a second algorithm, also employing a linear algorithm, can estimate systolic blood pressure and diastolic blood pressure. Thus, the sensor can measure all five vital signs along with hemodynamic parameters. It also includes a motion-detecting accelerometer, from which it can determine motion-related parameters such as posture, degree of motion, activity level, respiratory-induced heaving of the chest, and falls.

The present invention concerns a new category of integrated circuitry and a new methodology for adaptive or reconfigurable computing. The preferred IC embodiment includes a plurality of heterogeneous computational elements coupled to an interconnection network. The plurality of heterogeneous computational elements include corresponding computational elements having fixed and differing architectures, such as fixed architectures for different functions such as memory, addition, multiplication, complex multiplication, subtraction, configuration, reconfiguration, control, input, output, and field programmability. In response to configuration information, the interconnection network is operative in real-time to configure and reconfigure the plurality of heterogeneous computational elements for a plurality of different functional modes, including linear algorithmic operations, non-linear algorithmic operations, finite state machine operations, memory operations, and bit-level manipulations. The various fixed architectures are selected to comparatively minimize power consumption and increase performance of the adaptive computing integrated circuit, particularly suitable for mobile, hand-held or other battery-powered computing applications.

The present invention concerns a new category of integrated circuitry and a new methodology for adaptive or reconfigurable computing. The preferred IC embodiment includes a plurality of heterogeneous computational elements coupled to an interconnection network. The plurality of heterogeneous computational elements include corresponding computational elements having fixed and differing architectures, such as fixed architectures for different functions such as memory, addition, multiplication, complex multiplication, subtraction, configuration, reconfiguration, control, input, output, and field programmability. In response to configuration information, the interconnection network is operative in real-time to configure and reconfigure the plurality of heterogeneous computational elements for a plurality of different functional modes, including linear algorithmic operations, non-linear algorithmic operations, finite state machine operations, memory operations, and bit-level manipulations. The various fixed architectures are selected to comparatively minimize power consumption and increase performance of the adaptive computing integrated circuit, particularly suitable for mobile, hand-held or other battery-powered computing applications.

The present invention relates to a method for camera calibration through solving circular ring points image coordinates by utilizing a space regular tetrahedron. The method comprises the following steps: shooting an image containing 3 visible faces or shooting two images each containing 2 visible faces of a calibrating block; extracting a summit of each edge on the image and an image coordinate of each characteristic point on the image; determining vanishing point coordinates on the straight lines where the sides of triangles on each face are located; solving the image coordinates of circularring points on each face by utilizing the converse theorem of Laguerre theorem; establishing a constraint equation in regard to parameters in a camera by virtue of circular ring point images; and solving the parameters in the camera, including main point coordinates of the camera, effective focal length and inclination factors, by means of linear algorithms. The method for solving parameters calibrated in a camera through circular ring points by utilizing a regular tetrahedron provided by the present invention can solve all the parameters in a camera by means of linear algorithms according toan image. Utilizing a calibrating block of the present invention can realize automatic calibration and reduce the error caused by a measurement during the calibration process. At the same time, due to the stability of triangles, calibration precision can be improved during the calibration process of the camera.

Several algorithms are provided to estimate and remove relative clock skews from delay measurements based on the computation of convex hulls. The algorithms are linear in the number of measurement points for the case with no clock resets. For the more challenging case with clock resets, i.e., the clocks are reset to some reference times during the measurement period, linear algorithms are provided to identify the clock resets and derive the best clock skew lines. The algorithms are also extended to environments in which at least one of the clocks is controlled by Network Time Protocol. These algorithms can also be extended for active clock synchronization to replace or further improve Network Time Protocol.

The invention discloses a colorized CCD panoramic scanning imaging system and a system thereof, wherein the method comprises the following steps of: using a semi-spherical panoramic annular lens (PAL) to form an annular image; imaging by scanning of area-array CCDs or linear-array CCDs arranged along annular image; and transmitting images into a computer which joints the images for expanding a panoramic image. The system is that: the CCDs are arranged in a rotatable mechanical rotary table and are controlled by a motor to rotate, and the motor is controlled by a computer through a motor control circuit module, thereby controlling CCD rotary scanning panoramic imaging; the images captured is transmitted into a computer through a data transmission interface, and the computer uses an image processing program to joint the images and expands the images. The invention, by use of a computer vision technique, can create a real-time 360-degree panoramic image which has not only infinite depth of field, but also high resolution; a simple linear algorithm can perform orthoscopic calibration on the panoramic image. The invention is particularly applicable in real time monitoring, air defense, etc fields.

The present invention concerns a new category of integrated circuitry and a new methodology for adaptive or reconfigurable computing. The exemplary IC embodiment includes a plurality of heterogeneous computational elements coupled to an interconnection network. The plurality of heterogeneous computational elements include corresponding computational elements having fixed and differing architectures, such as fixed architectures for different functions such as memory, addition, multiplication, complex multiplication, subtraction, configuration, reconfiguration, control, input, output, and field programmability. In response to configuration information, the interconnection network is operative in real-time to configure and reconfigure the plurality of heterogeneous computational elements for a plurality of different functional modes, including linear algorithmic operations, non-linear algorithmic operations, finite state machine operations, memory operations, and bit-level manipulations. The various fixed architectures are selected to comparatively minimize power consumption and increase performance of the adaptive computing integrated circuit, particularly suitable for mobile, hand-held or other battery-powered computing applications. In an exemplary embodiment, some or all of the computational elements are alternately configured to implement two or more functions.

The invention discloses an intelligent traffic light based on the signal control processing technology and a signal control method. The intelligent traffic light comprises a video detection device, an image processing module, an optimizing timing calculation module, a control module and a traffic signal display module, wherein the video detection device, the image processing module, the optimizing timing calculation module, the control module and the traffic signal display module are connected in sequence. Firstly, the video detection device shoots practical road conditions, vehicle queuing images are obtained, boundary operators are extracted through the image processing module according to the digital image processing technology, and a current vehicle queue length is worked out according to a built vehicle queue length model; then, vehicle queue length information is transmitted to a communication port of a single chip microcomputer through wireless communication, and the optimal green light duration is worked out according to the current vehicle queue length through a linear algorithm embedded in the single chip microcomputer. According to the intelligent traffic light based on the signal control processing technology and the signal control method, the traffic light changes intelligently according to traffic flow, and therefore the purposes of reducing traffic pressure, saving energy and reducing emission are achieved.

The present invention presents a method for use with an acoustic sensor array comprised of a number of pressure-vector sensors capable of sensing the acoustic scalar field and acoustic vector field of an acoustic wave. The method is a signal processing technique that utilizes nonlinear processing of pressure-vector sensor signals in the acoustic sensor array. The method involves the steps of receiving the sensor output values, processing the output values using a non-linear algorithm to create a mathematical series of values, transforming the series, applying weighting to the series and performing a summation of the values in the series to calculate the array directivity response. The array directivity response can then be further processed where the array is part of a sonar system.

The present invention is a method for identifying unknown parameters in a system having a set of governing equations describing its behavior that cannot be put into regression form with the unknown parameters linearly represented. In this method, the vector of unknown parameters is segmented into a plurality of groups where each individual group of unknown parameters may be isolated linearly by manipulation of said equations. Multiple concurrent and independent recursive least squares identification of each said group run, treating other unknown parameters appearing in their regression equation as if they were known perfectly, with said values provided by recursive least squares estimation from the other groups, thereby enabling the use of fast, compact, efficient linear algorithms to solve problems that would otherwise require nonlinear solution approaches. This invention is presented with application to identification of mass and thruster properties for a thruster-controlled spacecraft.

The invention relates to an abdominal organ dynamic contrast enhanced magnetic resonance imaging method based on compressed sensing. The method concretely includes the steps: 1), a magnetic resonance imaging pulse sequence includes a three dimensional gradient echo excitation pulse, a space coding gradient and a signal relaxation sequence, the three of which are explained respectively as follows: 1.1) setting parameters of a radio frequency excitation pulse of a three dimensional gradient echo sequence; 1.2) optimizing a choose-layer phase coding kz and an inner-layer phase coding ky respectively, that is to say, carrying out sub-sampling according to a CS theory, the frequency coding direction kx being fully sampling; and 1.3) applying spoiled gradient to an x gradient direction, a y gradient direction and a z gradient direction in terms of the signal relaxation sequence; 2) a magnetic resonance imaging system carries out compressed sampling of k-space data of all phases of DCE-MRI scanning for an abdominal organ on the basis of a CS optimized magnetic resonance imaging pulse sequence, and obtains original sampling data of a time sequence; and 3) CS reconstruction of the original sampling data is conducted, that is to say, a DICOM image of the abdominal organ is reconstructed and obtained on the basis of a non-linear algorithm with a minimized 1<1> normal form. The method can be widely applied to abdominal organ dynamic contrast enhanced magnetic resonance imaging.

A new form of pattern referred to as a fully dependent pattern or d-pattern is provided. The d-pattern captures dependence among a set of items based on a dependency test. An efficient algorithm is provided for discovering all d-patterns in data. Specifically, a linear algorithm is provided for testing whether a pattern is an d-pattern. Further, a pruning algorithm is provided that prunes the search space effectively. Still further, a level-wise algorithm for mining d-patterns is provided.

A methodology for optimizing the placement of network “Points of Presence” (POPs) across the carrier's entire network (i.e., a “global” solution”) utilizes carefully constructed customer clustering and simulated annealing methodology to create a cost-efficient solution. The customer base is first partitioned into a plurality of clusters such that the customers within each cluster are closer to its centroid than the centroid of any other cluster (e.g., applying the k-means clustering algorithm or any other suitable method of partitioning the customer base). A linear algorithm process is used to minimize the costs associated with the number of placement of POPs within each cluster. A simulated annealing (SA) process is then used to iterate the entire set of potential POP locations until a compact, steady-state solution is achieved (or, alternatively, until a given number of iterations has been performed). In a preferred embodiment, a number of iterations are performed at each “temperature” in the simulating annealing process to further improve the result (this iterative process referred to in the art as “intensification”).

An application of three-dimensional imaging to the field of practical engineering such as nondestructive inspection, medical imaging, ground surface detection, geophysical exploration and the like is of great potential. As approximate treatment is adopted in a linear imaging algorithm, a reconstructed image is limited in precision and accuracy; and while in a non-linear algorithm such as a contrast source inversion (CSI) algorithm, position, shape and material parameters of an image such as an interested target can be gradually improved in an iteration process, and an image most similar to the interested target is reconstructed at last. The invention discloses a nonlinear imaging method for multi-frequency multi-transceiver three-dimensional electromagnetic actual measurement data based on the contrast source inversion algorithm combining a frequency hopping method with a regularization method. As forward calculation is not needed, a calculation amount for calculating a three-dimensional dyadic green function operator and a conjugate operator of the function operator in the iteration process is controllable, and a reconstruction result proves that the method can be widely applied to the field of practical applications with requirements of high-precision and high-resolution imaging due to precision and feasibility of an application to three-dimensional electromagnetic imaging.

The invention provides a joint prediction method of base station traffic. The problem that the traditional linear algorithm is bad in prediction performance when the traffic data is nonlinear and hasa sudden change value is solved. The method comprises the following steps: firstly collecting traffic data from a base station as a data set, performing data preprocessing on an abnormal value and a missing value; decomposing processed data by adopting wavelet transform, enabling the traffic data to be smooth and easy to predict; performing single reconstruction on a sequence obtained through decomposition, wherein a low-frequency signal is predicted by adopting an echo state network model, and a high-frequency signal performs prediction by adopting an autoregression integral sliding average model; and finally performing linear accumulation on the prediction numerical value of the single sequence to obtain a final result. Compared with the single model prediction, the joint model method disclosed by the invention can reach better prediction, the reduced average absolute percentage error can achieve 6%, and the normalization root mean square error is reduced to a certain degree; the traffic data prediction accuracy of the base station is improved, and the network resource reasonable allocation can be improved.

The invention provides a neck-worn sensor (referred to herein as the ‘necklace’) that is a single, body-worn system that measures the following parameters from an ambulatory patient: heart rate, pulse rate, pulse oximetry, respiratory rate, temperature, thoracic fluid levels, stroke volume, cardiac output, and a parameter sensitive to blood pressure called pulse transit time. From stroke volume, a first algorithm employing a linear model can estimate the patient's pulse pressure. And from pulse pressure and pulse transit time, a second algorithm, also employing a linear algorithm, can estimate systolic blood pressure and diastolic blood pressure. Thus, the necklace can measure all five vital signs along with hemodynamic parameters. It also includes a motion-detecting accelerometer, from which it can determine motion-related parameters such as posture, degree of motion, activity level, respiratory-induced heaving of the chest, and falls.

The invention provides a structural nuclear magnetic resonance image processing method used for Alzheimer disease early detection. The method includes the steps of firstly, conducting feature extraction on a structural nuclear magnetic resonance image expressed in a tensor form through a non-correlation multi-linear algorithm, then, conducting selecting on an extracted algorithm through the Laplacian value algorithm, and finally sending the selected feature into an SVM classifier and conducting training, classifying/diagnosing. According to the method, feature extraction is conducted on the structural nuclear magnetic resonance image through a tensor analysis method, spatial structure information of original data is reserved, the step of feature selection is added, redundant information in the feature is further reduced, and the feature with higher discernment is selected. According to experimental data, the method has high classification accuracy, and a possible auxiliary tool is provided for early diagnosis of the Alzheimer disease.