135 results about "Linear algorithm" patented technology

A magnetic resonance system is disclosed. The system includes a transceiver having a multichannel receiver and a multichannel transmitter, where each channel of the transmitter is configured for independent selection of frequency, phase, time, space, and magnitude, and each channel of the receiver is configured for independent selection of space, time, frequency, phase and gain. The system also includes a magnetic resonance coil having a plurality of current elements, with each element coupled in one to one relation with a channel of the receiver and a channel of the transmitter. The system further includes a processor coupled to the transceiver, such that the processor is configured to execute instructions to control a current in each element and to perform a non-linear algorithm to shim the coil.

The present invention relates to an apparatus and method for the non-invasive analysis of physiological attributes, such as heart rate, blood pressure, cardiac output, respiratory response, body composition, and blood chemistry analytes including glucose, lactate, hemoglobin, and oxygen saturation. Using a combination of multi-functioning disparate sensors, such as optical and electrical, improvements are made over existing physiological measurement devices and techniques. The special configuration of one or more multi-functional sensors is used to non-invasively measure multi-wavelength optical plus one or more of ECG, Bio-impedance, and RF-impedance spectroscopic data. This information is used to develop self-consistent, non-linear algorithm in order to derive the physiological attributes while compensating for various forms of interfering effects including motion artifacts, sensor attachment variability, device component variability, subject physical and physiology variability, and various interfering physiological attributes.

A method and system for tracking the minitype device in vivo are disclosed, wherein the system includes a built-in permanent magnet, a function sensor, a MPU, a wireless radio circuit and a minitype device in vivo of the transmitting antenna, and also includes as array detecting unit, a portable data logger, a vitro data receiving and processing system for the data processing and the displaying center. The vitro data receiving and processing system is used for receiving the minitype device data and the tacking orientation. The tracking method synthetizes a linear algorithm of the magnetic location, a nonlinear optimization algorithm, and a radio frequency antenna synthesis locating method, which can fast obtain the complete 6-dimension position orientation parameter of the vivo minitype device, tracks the position and the direction of the vivo minitype device in real-time, and ensures the accuracy, the reliability, and the real time of the system. The invention can provide the precise orientation and the movement trace, the direction and the speed information for the vivo minitype medical device, and also provides the important information about the symptom and the pathology parts etc.

The invention relates to an interest recommendation method and device, a server and a storage medium. The method comprises the following steps that: obtaining the characteristic information of a target user; according to the characteristic information, adopting an interest similarity prediction model to predict an interest similarity between the target user and a user group, wherein the interest similarity prediction model is realized on the basis of a tree model coding hybrid linear algorithm; according to the interest similarity, determining a recommended user which has the similar interestwith the target user in the user group; and obtaining the interest list of the recommended user, and creating a recommendation list for the target user. By use of the method, the problem of the cold boot of a traditional collaborative filtering algorithm can be solved, wherein the problem is a recommendation problem when the user does not have enough watching history. The accuracy of a recommendation result is improved, a click rate is obviously improved, and a purpose of "everyone has their own view" of personalized recommendation is realized.

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.

A reservoir prediction system and method are provided that use generalized EnKF using kernels, capable of representing non-Gaussian random fields characterized by multi-point geostatistics. The main drawback of the standard EnKF is that the Kalman update essentially results in a linear combination of the forecasted ensemble, and the EnKF only uses the covariance and cross-covariance between the random fields (to be updated) and observations, thereby only preserving two-point statistics. Kernel methods allow the creation of nonlinear generalizations of linear algorithms that can be exclusively written in terms of dot products. By deriving the EnKF in a high-dimensional feature space implicitly defined using kernels, both the Kalman gain and update equations are nonlinearized, thus providing a completely general nonlinear set of EnKF equations, the nonlinearity being controlled by the kernel. By choosing high order polynomial kernels, multi-point statistics and therefore geological realism of the updated random fields can be preserved. The method is applied to two non-limiting examples where permeability is updated using production data as observations, and is shown to better reproduce complex geology compared to the standard EnKF, while providing reasonable match to the production data.

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 discloses a ground data processing method for the radiometric correction of a remote sensing image taken by a double-sided mirror rotary multiple parallel-scan infrared camera. The method is based on the imaging principle of the double-sided mirror rotary multiple parallel-scan of an HJ-1B infrared camera, and solves the actual engineering problem of the data processing in a satellite ground system; the position of a damaged line is automatically detected by a DN value mapping-energy level statistical method, and the image recovery is carried out by the linear interpolation; aiming at the unevenness in a scan band caused by the multiple parallel-scan and the unevenness among the bands caused by the double-sided mirror scan, the multipoint piecewise linear interpolation fitting algorithm and the two-point linear algorithm are adopted for correction; aiming at the image dislocation between the adjacent scan bands caused by the double-sided mirror scan, the algorithm for minimizing the difference value of adjacent pixels is adopted for correction; and aiming at a vertical stripe appeared on the B2 waveband of the infrared camera after the satellite is launched, the first derivative gradient value method is adopted for automatic detection and recovery, thereby effectively eliminating the stripe and obviously improving the image quality.

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 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 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 technique provides for the detection of pace pulses in electrocardiogram data. The technique provides for processing one or more sets of electrocardiogram data via a non-linear algorithm. Furthermore, the technique provides for detecting one or more pace pulses in the one or more sets of electrocardiogram data via a non-linear detection algorithm. Systems and computer programs that afford functionality of the type defined by this method are also provided by the present technique.

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.