683 results about "Transfer matrix" patented technology

Calibrating a posture detector for a patient's body involves measuring outputs of one or more sensors disposed in relation to the patient's body while the patient assumes a plurality of positions. A transfer matrix is formed having coefficients corresponding to the measured outputs. The transfer matrix defines a relationship between a coordinate system of the one or more sensors and a coordinate system of the patient's body. The body coordinate system is used as a reference coordinate system for posture detection. Posture, including tilt and / or tilt angle, may be determined based on first and second rotational angles defined in relation to the body coordinate system.

A method in a computer for optimizing a dosage of intensity modulated radiotherapy (IMRT) comprises the steps of: dividing a three dimensional (3D) volume into a grid of dose voxels, wherein each dose voxel receives a dose of radiation from at least one pencil beam having a pencil beam weight and a gantry angle; selecting a first set of dose voxels from the 3D volume positioned within at least one of a planning target volume (PTV), organs at risk (OAR), and normal tissue in a neighborhood of the PTV; choosing a dose matrix from the first set of dose voxels; constructing a beam weight vector of individual beam weights for each pencil beam at each gantry angle; calculating a transfer matrix representing a dose deposition to the dose voxels from each pencil beam with unit beam weight; inverting the transfer matrix; performing a matrix multiplication of the inverted transfer matrix and the dose matrix and populating the beam weight vector with the results of the matrix multiplication; and iteratively modifying a plurality of doses in the dose matrix within a given range, wherein the range has a specific probability distribution function of acceptable dose values, and repeating the matrix multiplication until the negative weights in the beam weight vector are substantially eliminated, resulting in an optimized set of doses.

An automated tuning method of a large-scale multivariable model predictive controller for multiple array papermaking machine cross-directional (CD) processes can significantly improve the performance of the controller over traditional controllers. Paper machine CD processes are large-scale spatially-distributed dynamical systems. Due to these systems' (almost) spatially invariant nature, the closed-loop transfer functions are approximated by transfer matrices with rectangular circulant matrix blocks, whose input and output singular vectors are the Fourier components of dimension equivalent to either number of actuators or number of measurements. This approximation enables the model predictive controller for these systems to be tuned by a numerical search over optimization weights in order to shape the closed-loop transfer functions in the two-dimensional frequency domain for performance and robustness. A novel scaling method is used for scaling the inputs and outputs of the multivariable system in the spatial frequency domain.

An electrosurgical system including or connected to an output circuitry comprising an electrosurgical device and an electrical cable is modelled during a cable interrogation phase using a transfer matrix in order to determine a leakage capacitance in the electrosurgical system. After the leakage capacitance is assigned or set to a virtual capacitor in the transfer matrix, an output parameter of the electrosurgical system, such as output voltage, output current, output impedance or output electrical power, may be determined by applying an actual input voltage to the output circuitry and measuring a resulting input current, and multiplying the input voltage and measured current by the transfer matrix.

An apparatus for and a method of iterative equalization for communication over noisy channels suitable for use with a wide range of different types of communications systems and channels that is particularly applicable to power line based communication systems. Equalization of received symbols is achieved by iteratively removing the influence of previous symbols dispersed due to channel ISI. Equalization is performed using iterative subtraction in combination with calculations based on the inverse of the transfer matrix. The impulse response of previous symbols is subtracted out to yield the impulse response of the received symbol. The estimate of the current symbol {tilde over (B)}n is then calculated by passing the modified received symbol through a matched filer which functions to remove the effect of channel ISI from the symbol. Multiple iterations are performed to improve the accuracy of the resultant symbol decision.

The present invention discloses an automatic calibration method for a robot system, comprising steps of: calibrating intrinsic parameters of a sensor and a sensor coordinate system of the sensor with respect to a world coordinate system by means of a calibration plate; and controlling a robot under the guidance of the calibrated sensor to move an original point of a tool coordinate system of a tool mounted on the robot to reach the same target point with a plurality of different poses, and calculating a transfer matrix tcpTt of the tool coordinate system with respect to a tool center point coordinate system of the robot based on pose data of the robot at the same target point. The robot can accurately move to the same target point with the plurality of different poses, improving the calibration accuracy of the robot system. Furthermore, the calibration of the robot system is automatically performed by a control program, increasing the calibration efficiency, and simplifying the calibration operation.

In MIMO transmission which executes quadrature modulation of M transmission antennas and N reception antennas, a transmission signal vector will be set as a vector having the element number of 2M that comprises the in-phase components and quadrature components of M complex signals, a reception signal vector will be set as a vector having the element number of 2N that comprises the in-phase components and quadrature components of N complex signals, and a transfer matrix will be set as a real matrix comprising 2N rows and 2M columns. Then, a transfer matrix containing IQ mismatch is obtained based on a training signal, thereby executing MIMO encoding and decoding. For learning of the transfer matrix, a training signal which has two linearly-independent signal points on a constellation for each of the transmission antennas is used. With such arrangement, it is possible, in MIMO wireless data transmission, to compensate deterioration in a bit error rate that is caused by IQ mismatch in a quadrature modulator and a quadrature demodulator.

The invention discloses a cloud computing based real-time mass user behavior analyzing method and system. User behaviors and context data are collected by a client end in real time and pre-processed and clustered on the basis of a MapReduce model; ontology data are subjected to reasoning, and latest interests of users are analyzed in real time; a track recurrence algorithm on the basis of a user behavior context is provided for track filling; interest similarity of users is computed by a cosine factor method, an interest similarity matrix is established; a Markov transfer matrix and a collaborative filtering based Markov recommendation model are established to realize effective and precise recommendation. The user behaviors and context information are subjected to model establishment via ontology, and semantic-level sharing and reusing of large-scale behavior information are achieved via an Hbase (hadoop database) based ontology memory mode. Technologies of cloud-computing, the ontology, reasoning and knowledge discovering are combined, and problems in instantaneity, efficiency, large-scale memorizing and intelligentization in mass user behavior analysis are solved.

The invention belongs to the technical field of navigation, and concretely relates to an inertial navigation / mileometer autonomous integrated navigation method. The method comprises the following steps: 1, initially aligning an inertial navigation system, and initializing parameters of a Kalman filter; 2, carrying out inertial navigation calculation to obtain a discrete state transfer matrix and a measurement matrix; 3, calculating based on the summation measurement of displacement errors to obtain a filtering observation; 4, carrying out mileometer information fault detection; 5, carrying out Kalman filtering; and 6, correcting. The method solves technical problems of too large mileometer quantification noise and reduced combination navigation precision of present inertial navigation / mileometer integrated navigation methods; and the method which adopts a displacement integration coupling based inertial navigation / mileometer integrated navigation strategy abandons a quantization noise introduced in the traditional methods utilizing a speed, which is obtained by performing calculation on a displacement, as an observation, and substantially improves the reliability of an integrated navigation system.

Strategies are described for processing image information using a data structure which conveys color information. The color information describes color-related formatting applied to the image information. The data structure can be passed down a video processing pipeline, where each functional component in the pipeline can draw color information from the data structure to improve the accuracy of its processing. Further, each component can supply previously unknown color information to the data structure for use by other (downstream) components in the pipeline. Exemplary fields of the data structure can include one or more of: a video transfer function field; a color primaries field; an image light field; a transfer matrix field; a nominal range field; and a video chroma sampling field. The transfer matrix field can be used to convert image information from one color space to another, such as a luma-related color space to an RGB-related color space. Processing operations can be performed on progressive and linear RGB image information.

The invention discloses a deep learning-based quick automatic capture and placement method. The method can quickly and accurately determine positions and attitudes of articles in combination with a GPU and a 3D camera by adopting a deep learning scheme. Through a quick calibration scheme, a transfer matrix from a coordinate system of the 3D camera to a coordinate system of a mechanical arm can beobtained. The transfer matrix can convert the positions and attitudes of the articles to the coordinate system of the mechanical arm, and then operate the mechanical arm to perform capture. For accurately placing the articles in a specific mode, the articles are subjected to secondary attitude estimation. A secondary attitude estimation process comprises the steps of firstly capturing the articlesto an estimation position by fixed attitude; at the moment, segmenting out the articles more completely by only using depth information; projecting the articles to a placement plane; and performing accurate attitude estimation for information on the plane, thereby enabling the mechanical arm to perform placement.

The invention relates to a method for filling indoor LiDAR missing data based on Kinect. The method comprises extracting a key frame in a Kinect scanning process to obtain sparse scanned data; using a scale invariant feature transform (SIFT) algorithm to perform feature extraction on a RGB-D image collected by a Kinect device, and rejecting abnormal feature matching points through a random sample concensus (RANSAC) operator; merging the extracted features; extracting features of an LiDAR image, matching the features with the features of the Kinect device roughly to obtain a transfer matrix; using an improved iterative closest point (ICP) algorithm to achieve fine match of the LiDAR image with the RGB-D image of the Kinect; and performing the missing data fusion between an LiDAR model and the part scanned by the Kinect. The method for filling indoor LiDAR missing data based on Kinect has the advantages that the device cost is low, the acquisition process is flexible, scene depth and image information can be obtained, partial or missing data of indoor complex scenes can be acquired and filled rapidly.

The invention discloses a method for calibration of a workpiece coordinate system. The method for calibration of the workpiece coordinate system comprises the steps that (1) an original point of a tool coordinate system of an industrial robot moves to random three points, not collinear, in a workpiece coordinate system of the industrial robot to obtain workpiece coordinates, in the workpiece coordinate system, of the three points and base coordinates, in a base coordinate system of the industrial robot, of the three points, (2) direction vectors of the three workpiece coordinates and direction vectors of the three base coordinates are obtained according to the workpieces coordinates and the base coordinates of the three points respectively, and (3) a homogeneous transfer matrix of the workpiece coordinate system relative to the base coordinate system is obtained according to the direction vectors of the three workpiece coordinates and the direction vectors of the three base coordinates to accomplish calibration of the workpiece coordinate system. The invention further discloses a device for calibration of the workpiece coordinate system and a method and device for workpiece processing. According to the mode, the method and device for calibration of the workpiece coordinate system and the method and device for workpiece processing can simply and rapidly achieve calibration of the workpiece coordinate system, and is good in operability.

The invention discloses an object grabbing region positioning method based on point cloud registering. The positioning method comprises a preprocessing part and an object grabbing positioning part. The preprocessing part comprises establishment of a three dimensional model point cloud library and generation of an SVM classifier. The object grabbing positioning part mainly comprises original image data acquisition of a to-be-grabbed object, image segmentation based on region increasing, region screening of the to-be-grabbed object, generation of Point Cloud data, point cloud registering, and transformation of a grabbing region marked on a cloud point Model by use of transfer matrix Transform and reflection of the changed grabbing region to a 2D image through a built-in camera of a real-sensing 3D camera, thereby finishing grabbing of the object. During the cloud point registering, coarse matching is performed by use of the RANSAC algorithm, and fine tuning is performed by use of the ICP algorithm. According to the invention, desktop-level objects can be automatically detected and positioned; the positioning precision is high; and results are output within seconds without usage of a GPU operation unit.

The invention provides a coarse alignment method for a fiber optic gyro strapdown inertial navigation system based on single axis rotation. The coarse alignment method comprises the following steps: (1) determining initial position parameters of a carrier by a GPS; (2) collecting the data output by a fiber optic gyroscope and a quartz accelerometer and processing the data; (3) determining a transfer matrix Ti<n> of a navigation coordinate system and an inertial coordinate system according to the mutual position relation of the coordinate systems; (4) allowing a single axis of an inertial measurement unit to continuously rotate, setting superposition of an initial time IMU coordinate system s and a carrier coordinates b, then allowing the inertial measurement unit to continuously rotate around a positive direction of an azimuth axis ozb of the carrier coordinate system with an angular velocity Omega=6 degrees / s; (5) determining the relative position relation of the inertial coordinate system and a base inertial coordinate system; and (6) determining an expression of a strapdown matrix after coarse alignment is over according to the calculated relative conversion relation of the coordinate systems calculated in step (3), (4) and (5). The coarse alignment method can help obtain higher coarse alignment precision under a swinging interference condition.

The invention provides a method for initial alignment of a single-axis rotation strap-down inertial navigation system (SINS). The method comprises the following steps: building a carrier coordinate system and computing a transfer matrix between geographic coordinate systems on the basis of coarse alignment completed by collecting the information output by gyroscopes and accelerometers in the SINS with the carrier being in a static state; establishing Kalman filtering state equations with speed errors as the state variables and measurement equations with the speed errors as the measurement variables; and estimating the misalignment angles of the carrier by the Kalman filtering technique and feeding back to the SINS to complete the initial alignment of the SINS. The invention can overcome the influence on the estimation precision of the azimuth misalignment angles caused by the equivalent gyroscope drift of the geographic coordinate systems and improve the alignment precision.

The invention relates to apparatus for measuring color, the apparatus comprising: an acquisition system including a video camera and processing means organized to respond to the signals delivered by the camera to determine the tristimulus values of the color of the object in a reference colorimetric system by using a transfer matrix to transform the colorimetric system associated with said acquisition system into the reference colorimetric system, and to determine a correction function Γ to correct the non-linearities of said acquisition system.

The invention discloses a deep network compression method based on dimensional adaptation adjusting Tucker decomposition. The method comprises a dimensional adaptation adjusting process and a dimensional adaptation weight tensor decomposition process. Through adaptively adjusting a size of each dimensions of a tensor, a new any order tensor is generated. Through a learnable nuclear tensor and a transfer matrix, tensor decomposition is realized so that a purpose of network optimization compression is reached. Compared to an existing low rank compression method, by using the method of the invention, under the condition that network performance is maintained, a network parameter quantity has a greater compression multiple and a higher compression multiple can be acquired. Simultaneously, a guiding position of a nonzero element does not need to be stored, an index does not need to be recorded and a storage space can be effectively used.

The invention relates to a handheld laser three-dimension scanning method based on single-camera mark point trajectory tracking. The handheld laser three-dimension scanning method comprises the following steps: (1) identifying and extracting the two-dimension position information of mark points in an image shot by a single camera, pre-judging according to the motion trajectories of the mark points in frames with a preset amount to obtain target positions in a current frame, then searching around the target positions to obtain mark points corresponding to the target positions, and establishing an initial matching relationship between the mark points in the current frame and an original mark point library; (2) utilizing the initial matching relationship to calculate the RT transfer matrix of an instrument from a current relative coordinate system Oc to a world coordinate system Ow, and utilizing a reprojection method for checking the previous initial matching relationship; (3) extracting a laser projection contour in a current frame image, and converting to three-dimensional coordinates under the world coordinate system Ow through the RT transfer matrix. The invention also discloses handheld laser three-dimension scanning equipment. According to the method and the equipment, the requirement for system hardware configuration is reduced, the smoothness during moving and splicing is good, the precision is relatively high, and the cost is relatively low.

The invention relates to a method for simply and easily calibrating an industrial robot. The method comprises the following steps of: establishing an industrial robot kinematics model, and solving a robot kinematics pose transfer matrix; extracting a robot end position component, and calculating an error transfer matrix; operating a robot end clamp to contact four side edges of a standard cube, reading a code disc number of each joint of the robot, and calculating a position coordinate; changing the pose of the standard cube, reading the code disc number of each joint of the robot again, calculating the position coordinate, and repeating the step for many times; and listing position coordinate matrix equations with an identification parameter, and arranging the position coordinate matrix equations in a manner of Ax=b, wherein A is of a matrix type, x is a column vector with the identification parameter, and b is the column vector, and if A is not strange, a parameter to be identified is solved, and the original parameter is corrected by using the identification result. The method disclosed by the invention has the advantages of convenience, practicability, lower cost, more simpleness on operations, capability of reaching a higher precision, and unnecessity of buying high-precision equipment, such as a high-precision laser instrument and a vidicon.

The invention discloses a calibration method of a laser galvanometer processing system under the guidance of binocular stereoscopic vision. The calibration method comprises the following steps: predetermining a laser galvanometer processing pattern containing a plurality of two-dimensional mark points; acquiring dense space mark points in different depths in a depth-of-field of the laser galvanometer processing system through laser marking by adopting the laser galvanometer processing pattern; measuring by a binocular vision sensor to obtain three-dimensional coordinates of each space mark point; acquiring a transfer matrix representing a mapping relation between the binocular vision sensor and the laser galvanometer processing system according to the correspondence relation between coordinates of the corresponding two-dimensional mark point on the laser galvanometer processing pattern and the three-dimensional coordinates of the corresponding space mark point. According to the calibration method disclosed by the invention, the robust mapping relation between the binocular vision sensor and the laser galvanometer processing system can be effectively established, and the vision feedback processing precision is improved. The calibration method is convenient to operate and high in stability.

The invention discloses a vehicle operating condition multi-scale predicting method based on the Markov chain. The method establishes a Markov chain prediction model for the vehicle operating condition. The method comprises the steps of computing a state transferring matrix by maximum likelihood estimation according to the history information of vehicle operating condition; performing the vehicle operating condition predicting of different time scales according to the obtained state transferring matrix by utilizing the Markov chain and Monte Carlo analogy method; restoring the predicted outcomes of different time scales into data under a history operating condition sampling frequency through linear interpolation; dividing the predicted outcomes of different time scales into different confidence grades according to simulated sample quantity, and computing the linear weight coefficient under different confidence grades of the predicted outcome every time by adopting a linear weighting method; and merging all the predicted values of each scale of predicted outcome every time according to the weight coefficients and merging the different scales of predicted outcomes under the original data frequency to obtain the vehicle operating condition multi-scale predicting outcome. The vehicle operating condition multi-scale predicting method based on the Markov chain can meet the predicting precision requirements of the vehicle operating condition and the requirements of vehicle real-time control.

Systems, apparatus, and methods for controlling environmental maintenance modules (e.g. HVAC units) using sensors are provided. Values measured by the sensors can be used to determine a change in operation levels of the modules to keep the sensor values within a desired range. For example, a stopped module can be increased or started for more cooling when a sensor temperature is too hot. The module predicted to have the greatest effect on the temperature of hot sensor can be started. A transfer matrix, which provides a relation between a change in operation level and resulting sensor changes, can be used to perform the above predictions. As another example, a module can be stopped (or otherwise have an operation level decreased), if the sensor temperatures are within range, and the decrease in operation level is predicted not to cause an out-of-range condition.

A posture-fixing system for the mini-system which can realize the arbitrary movement; the system is characterized in that comprises a micro-magnetic sensor MMS module, a micro-inertia measurement unit MIMU module, a GPS module and a Kalman filtering module. Under the arbitrary state of motion of the mini-system, the MIMU module can work out the gravitational acceleration of the mini-system via the strapping of the output data and the navigation algorithm; the MMS module revolves the roll maneuver angle, the pitch angle and the 3D attitude information of the course angle for the mini-system via the real-time posture-fixing algorithm; also, the constant false alarm CFAR wave filter is adopted to filter the noise in the output speed and the acceleration information of the GPS. On one hand, the 3D posture information is sent to the Kalman filtering module for combination with the position and velocity information of the GPS, so as to correct the MIMU error from time to time via the information mixing algorithm, on the other hand, 3D posture information is adopted to replace the Cnb coordinate transfer matrix in real time; the Cnb coordinate transfer matrix will be delivered to the MIMU module and the GPS module, so that the horizontal coordinate system information is transferred to the carrier coordinates. The utility model introduces the iterative solution among the GPS, the MIMU and the MMS, so as to ascertain the direction of the moving vehicle under arbitrary state of motion. Therefore, the wide application prospects are available.

The invention discloses a high-precision near-field acoustic holography algorithm adopting a weighted iteration equivalent source method, which is characterized in that a holographic plane H is arranged in a sound source near-field radiation area, and sound pressure PH on the holographic plane H is measured; an equivalent source plane Se is arranged at the side, which is away from the holographic plane H, of an object reconstruction plane T, and equivalent sources are arranged on the equivalent source plane Se; a relation between the sound pressure PH and each equivalent source is established by using a sound pressure transfer matrix between the equivalent source and the holographic plane H; and the source intensity Q of each equivalent source is solved by adopting a new iterative regularization algorithm with a posteriori weighted norm constraint penalty term, and then sound field data on the object reconstruction plane T is calculated by using the solved source intensity Q and the transfer matrix between the equivalent source and the object reconstruction plane T. According to the invention, the source intensity of each equivalent source is precisely solved by using the new iterative regularization algorithm with the posteriori weighted norm constraint penalty term, thereby avoiding source intensity energy leakage caused by a 2-norm penalty term in the Tikhonov regularization process. Compared with conventional equivalent source based near-field acoustic holography, a calculation result acquired by the method disclosed by the invention is more accurate.

Calibrating a posture detector for a patient's body involves measuring outputs of one or more sensors disposed in relation to the patient's body while the patient assumes a plurality of positions. A transfer matrix is formed having coefficients corresponding to the measured outputs. The transfer matrix defines a relationship between a coordinate system of the one or more sensors and a coordinate system of the patient's body. The body coordinate system is used as a reference coordinate system for posture detection. Posture, including tilt and / or tilt angle, may be determined based on first and second rotational angles defined in relation to the body coordinate system.

A method, system and device for use in conjunction with Digital Subscriber Line (DSL) transmission systems, including Far-End Crosstalk (FEXT) cancellation circuitry. According to embodiments of the invention there is provided a system including a central office having a plurality of central modems, and at least one remote modem in communication with the plurality of central modems, the remote modem capable of automatic channel adjustment, and further capable of providing to the central office a channel adjustment parameter, wherein the central office includes a precoder to selectively precode symbols prior to transmission by each of the central modems with an estimation precoding matrix, and a controller to receive from the at least one remote modem respective channel adjustment parameters in response to transmitted symbols precoded with said estimation precoding matrix.

The invention aims at providing a sound field rebuilding method. The sound field rebuilding method comprises the following steps that firstly, a sound pressure value of a measuring face in a measuring sound field is measured; secondly, different sound sources are endowed with a certain weight through the centroid method according to the actual positions of the sound sources and the sound intensity, the positions and number of multi-ball virtual source intensities and the position coordinates of each virtual ball are calculated; thirdly, zero filling expanding is carried out on the measured sound pressure value of the measuring face to obtain the sound pressure value of an expanding face of the measuring face; fourthly, a transfer matrix between the sound pressure value of the expanding face of the measuring face and the virtual ball sound pressure is calculated; fifthly, a transfer matrix between the sound pressure value of a rebuilding face and the sound pressure value of the multi-ball virtual equivalent source intensities is built; sixthly, the transfer matrix obtained in the fourth step and the transfer matrix obtained in the fifth step are combined, and the sound pressure value of the rebuilding face is obtained. According to the sound field rebuilding method, multi-ball region two-dimensional fast Fourier conversion algorithm is introduced, a virtual source intensities configuration and the measuring face do not need to be conformal, and the calculation efficiency and calculation precision are very high.

The invention relates to a vector-quantization-based overall and local color image searching method. The invention provides a new color image searching method, and relates to the field of an image processing technology. The method comprises the steps of converting an RGB (red, green and Blue) color space into an HSV (Hue, Saturation, Value) color space, performing relatively accurate clustering division on the color space by applying a neural-network-based competitive learning algorithm training code book; describing a space distribution situation of colors by introducing a color transfer matrix; combining the two characteristics, namely an index column diagram and a main color transfer matrix, so as to perform the similarity measurement; processing images by applying a morphological opening-and-closing operation, highlighting a target contour so as to extract a local interest area so as to highlight an important area and limit background information. The color image searching method overcomes the defects that the color space distribution description is not enough and the background information cannot be effectively limited by using the overall color histogram method. By using the vector-quantization-based overall and local color image searching method, the color quantization is relatively accurate, the matching effect is relatively good, and the vector-quantization-based overall and local color image searching method is an effective method for further improving the researching efficiency.

The invention provides a noise source identification method adopting vibration speed measurement and a partial near-field acoustical holography method.. The method comprises the following steps of: measuring the vibration speed of a normal mass point on a finite aperture measurement surface H positioned at a near field; performing zero-padding expansion on the vibration speed; calculating a transmission matrix between the measurement surface and a sound source surface; and finally calculating so as to obtain sound pressure on the sound source surface S and the vibration speed of the normal mass point. The vibration speed of the normal mass point is used as an input value for sound field reconstruction, so that sound field information with relatively high precision can be acquired. Compared with the conventional iterative partial near-field acoustical holography method, the method adopting the partial near-field acoustical holography method has the advantages of being simple in calculation operation, short in calculation time, high in calculation efficiency and the like and is used for identifying and positioning a noise source and reconstructing a sound field.