87 results about "Sequence point" patented technology

The invention provides an apparatus for extracting a common structure from two three-dimensional structures each formed from a set of sequenced points. The apparatus is constructed so as to extract one of common portions with which the common portion length of the two point sets superposed with each other exhibits a greatest length and the cumulative sum of distances between matched points of the two point sets superposed with each other exhibits a lowest value as an optimum common structure. The common structure extraction apparatus is suitably used to analyze a molecular structure to make clear a mechanism for manifestation of a function of a substance in order to investigate a property of a novel substance such as a protein or artificially produce a novel substance in the fields of physics, chemistry and so forth.

The invention discloses a correction method of errors measured by a distributed raman optical fiber temperature measuring system. The correction method comprises the following steps: 1, determining sequence point number and signal intensity of a stokes signal and an anti-stokes signal; 2, performing optical fiber length normalization processing on the sequence point positions of the stokes signal and the anti-stokes signal; 3, calculating anti-stokes signal intensity by adopting an interpolation algorithm after signal position normalization, and obtaining the anti-stokes signal intensity at the same position with the stokes signal. The method is simple to realize, the anti-stokes signal is corrected by a piecewise cubic hermite interpolating polynomial algorithm, dispersion errors can be completely eliminated, and the measuring accuracy is improved greatly. Ideal results are obtained; for the long-distance distributed temperature measuring system, the method is outstanding in advantage and has an important value.

The invention discloses a gesture identification method based on a recursive model. The method comprises the basic steps of: 1, carrying out preprocessing on static and dynamic gesture images; 2, extracting static and dynamic gesture space sequences; 3, according to the gesture space sequences, constructing a gesture recursive model; and 4, by the gesture recursive model, carrying out gesture classification. According to the gesture identification method disclosed by the invention, in a form of converting the gesture space sequences into the recursive model, problems caused by different lengths of acquired gesture space sequences and incomparability of data values of sequence points are effectively solved, and robustness of a gesture identification algorithm is improved.

The invention discloses a control method of an industrial robot demonstration planner with a motion planning function. The method comprises: establishing a new demonstration file or opening a demonstration file, setting the system parameters and demonstration parameters of a robot, controlling the robot in a robot task space to carry out hand-operated demonstration, and utilizing the programming instruction of a VAL-III language to carry out demonstration programming; performing robot kinetics inversion, converting a three-dimensional locus into a joint space locus, inserting a locus intermediate point in the joint space locus, planning a locus equation, and obtaining the locus equation of a joint space; carrying out time interval interpolation calculating, and obtaining a robot control sequence point; and sending the obtained robot control sequence point to a robot controller through an RS-485 serial port. According to the invention, a demonstration system and a motion planning system are integrally combined, a robot motion planning function is provided, and the demonstration working efficiency is high.

The invention discloses a geographical location prediction method based on a continuous time sequence Markov model. The method comprises the following steps: step 1, filtering and clustering the original user trajectory data to generate a series of candidate locations; step 2, converting the user trajectory data into a [time T, location L] sequence according to the information of the candidate locations; step 3, implementing Gaussian mixture modelling on the sequence density of each location, and improving an original Markov model in combination with a transition probability matrix, a sequence point probability and other information to establish a Markov model based on a continuous time sequence; and step 4, predicting the geographical location of a target time point by using the Markov model based on the continuous time sequence. By adopting the technical scheme disclosed by the invention, the accuracy of prediction can be improved.

The invention discloses an identity authentication method and apparatus. The method comprises: employing an acceleration data sequence collected in authentication gesture implementation as a test sample sequence; pre-treating the test sample sequence; sectionalizing the pretreated test sample sequence; for each acceleration data sub-sequence after sectionalization, determining that the acceleration data sub-sequence represents an empty gesture when the mean value of the acceleration data sub-sequence is smaller than a preset threshold value, and removing all acceleration data sequence points included by the acceleration data sub-sequence from the test sample sequence; quantifying the difference between a reference sample sequence and the test sample sequence having empty gestures removed; determining authentication to be successful when the difference is no greater than a preset value; and determining the authentication to be failed when the difference is greater than a preset value. The method and apparatus can automatically determine the acceleration data sequence representing effective gestures, avoid the noise interference caused by operating buttons, and thereby improve identity authentication accuracy.

The invention discloses an image Gamma correction method for creating a lookup table based on the Taylor series fitting. The method comprises the following sequential steps: determining a pre-compensation characteristic function according to a given Gamma value and the maximum input image depth value, determining leading discrete sampling points according to the preset accuracy requirement, conducting Taylor series expansion on the leading discrete sampling points, calculating and storing Taylor series fitting multinomial coefficients at the positions of the leading discrete sampling points to obtain a discrete lookup table, utilizing the multinomial interpolation method for determining color lookup values at the positions of sequence points between all the adjacent leading sampling points to obtain a complete lookup table, inputting the depth of an image, and conducting Gamma correction on the image according to the complete lookup table. The image Gamma correction method for creating the lookup table based on the Taylor series fitting is strong in compatibility, small in pre-storage table, low in storage requirement and high in precision.

The invention relates to a method used for optimizing the electric network hydropower spinning spare capacity in the real-time dispatching. The method utilizes an EMS system to acquire the real-time electric network load data, and the ultra short-term load prediction is performed after preprocessing; the curve fitting is performed to a sequence formed by the real-time load and the predicted data based on the least square to obtain the absolute value of the maximum deviation between the sequence point and the curve, and the absolute value is determined as the hydropower spinning spare capacity of the next segment; and the no-load quotative discharge under the current water head of a hydropower generating unit is divided by the full output quotative discharge and then multiplied by the full output (i.e. the spinning spare capacity of the hydropower generating unit) to obtain a start-up ordering coefficient, and a machine set combination with the minimum energy consumption and the reserve capacity meeting the requirement is obtained by a heuristic searching algorithm. The method has the advantages that the method changes the traditional method of determining the hydropower spinning spare capacity according to a load coefficient and reduces the no-load reserve capacity of the hydropower; and the method utilizes the no-load energy dissipation coefficient to guide the start-up of the hydropower generating unit, further optimizes the economical operation of the hydropower generating unit and achieves the purposes of energy conservation and emission reduction.

The invention provides a video preview anycast method based on multipoint touch-control technique. The method comprises the following steps that: a user performs touch operations in at least two different directions, and a touch signal capturing module captures touch signals generated by the touch operations; a touch signal integrating module receives the touch signals and integrates the touch signals into initial track signals; a touch signal processing module generates smoothness-tendency track signals; a touch signal filtering module performs sequence point-checking according to equal intervals to generate signal set values capable of being identified by an application layer; a response touch-control module performs switching according to the signal set value of a first time point to obtain film source information, and switches film source information into width-height values of a displayed picture according to the signal set value of a follow-up time point; a video preview module enters a preview mode according to the received information; and a video anycast module enters a formal play mode or a mode for returning to a video list after user operations are finished. The multipoint touch-control technique-based video preview anycast method can respond to multipoint touch-control operations of the user to realize the preview anycast of videos, and improve the operating experience of the user.

The invention provides a three-dimensional positioning method of lightning based on stereoscopic vision, which is applicable to space reconstruction and three-dimensional positioning of lightning and relates to the fields of computer vision and aerospace and the like. The three-dimensional positioning method provided by the invention adopts a stereoscopic vision technology to carry out three-dimensional positioning on the lightning in the space and displays the development process of the lightning intuitively according to a two-dimensional image of the lightning so as to make further exploration and early warning for the lightning activity. The three-dimensional positioning method comprises the following steps of: (A) setting up a binocular stereoscopic-vision hardware system, and calibrating relevant parameters of a camera; (B) collecting and pre-processing lightning images; (C) segmenting and extracting a lightning skeleton line; (D) matching lightning sequence points of left and right images; (E) calculating a space three-dimensional coordinate of the lightning by utilizing a binocular stereoscopic-vision measurement model.

Arrangements described herein relate to inserting implicit sequence points into computer program code to support debug operations. Optimization of the computer program code can be performed during compilation of the computer program code and, during the optimization, implicit sequence points can be inserted into the computer program code. The implicit sequence points can be configured to provide virtual reads of symbols contained in the computer program code when the implicit sequence points are reached during execution of the computer program code during a debug operation performed on the computer program code after the computer program code is optimized and compiled.

The invention provides a multipoint-touch-technology-based video scaling method. A flow for implementing the method comprises the following steps that: a user performs at least two paths of touch operations in different directions, and a touch signal capturing module captures the touch operations, and generates touch signals; a touch signal integration module receives the touch signals, and integrates the touch signals into a primary track signal; a touch signal processing module forms a track signal tending to be smooth; a touch signal filtering module performs sequence point extraction according to a time interval, and generates signal group values recognizable for an application layer; a touch response module converts the signal group values of each time point into the initial locationand width and height values of the display of a video picture; a video scaling module converts data displayed by a video; and a video display module renders pictures obtained by the scaling of the video at each time point on a display screen until the processing of the signal group values of each time point is finished. By the method, the previewing and selective playing of the video can be realized in response to the multipoint touch operations of the user, and the operating experiences of the user are improved.

The invention provides a prediction method for wind power ramp. The prediction method comprises the steps that the ramp continuous time, the ramp amplitude and ramp direction of wind power in an ultra short period as well as the real-time ramp rate are calculated sequentially point by point, and the real-time ramp rate is compared with a threshold to determine whether a wind power ramp event occurs; a short-period wind power prediction sequence which is updated every day is obtained, smoothing is carried out on the prediction sequence point by point, the ramp center time of the power ramp event is determined according to the maximum of the part exceeding the set threshold, and the ramp continuous time, the ramp amplitude and the ramp direction are calculated according to the critical point exceeding the threshold, thereby realizing prediction for the extreme short-period wind power ramp event; and historical prediction / observation results for the ultra-short-time wind power ramp and the short-time wind power ramp are respectively calculated to predict the wind power ramp.

The invention discloses a method for reducing the non-uniqueness of an electromagnetic sounding inversion result. The method comprises the following steps: acquiring the electromagnetic sounding data of an exploration area to obtain at least over two two-dimensional inversion depth-resistivity models; performing regularization to obtain regularized two-dimensional depth-resistivity model inversion results; determining a learning sample and a target sample; establishing a BP (Back Propagation) neural network system; inputting the inner section of the area into a neural network in sequence point after point and depth point after depth point to obtain the desired prediction results of each measuring point and each depth point; reducing the prediction results into a real inversion resistivity value to obtain an optimized two-dimensional inversion result. According to the processing method for rapidly optimizing the inversion non-uniqueness of electromagnetic sounding data, neural network processing is performed on a plurality of inversion results, and known information is learned, so that the non-uniqueness is reduced, and the method is practical and effective for obtaining a real model of a complex area target body.

The invention provides a jump code transmission method in sparse code multiple access based on a time-varying codebook, which belongs to the technical field of non-orthogonal multiple access. The method comprises the steps that when each user registers a network, the user ID, a fixedly used pilot sequence and a jump code sequence pointed by the pilot sequence are assigned; when the user carries out data transmission, the pre-assigned pilot sequence is first sent; the user codes and groups data information to be transmitted to acquire SCMA blocks; the SCMA blocks are transmitted according to the codebook appointed by the jump code sequence; a receiver decodes the pilot sequence, identifies the access user and acquires the collision of the codebook; a decoder decodes each SCMA block according to the decoding complexity threshold established by the receiver to acquire the log likelihood ratio of the SCMA block; and each access user ID and the corresponding transmission data information are finally acquired. According to the invention, the SCMA transmission accuracy is improved; the decoding complexity is reduced through additional accuracy compromise; and delay is reduced.

An unmanned vehicle obstacle avoidance method based on a laser radar comprises the following steps: firstly, a global path is planned and a plurality of sequence points is selected on the global pathto form a sequence point set; secondly, an unmanned vehicle travels according to the global path, and the following steps are performed during the traveling process: an R60 is used to obtain the real-time latitude and longitude information and direction angles of the unmanned vehicle; the vehicle speed is reduced when the unmanned vehicle is close to the sequence point; after the sequence point isreached, the sequence point is deleted from the sequence point set, and then the unmanned vehicle is driven to the next sequence point until the unmanned vehicle goes through all the sequence point set; a controller sends an obstacle scan request to the laser radar, and the laser radar responds to the obstacle scan request to obtain obstacle information; and when the obstacle is scanned, a control strategy is executed. According invention, obstacles are monitored in real time through the front laser radar, and the obstacles are avoided through the control strategy together with a PID-P algorithm. The obstacles at different distances are avoided through the method according the obstacle information returned by the front radar. The method is simple and highly efficient, is stable in performance and reduces the obstacle avoidance cost for the unmanned vehicle.

The invention discloses a time sequence detection method and device, equipment and a storage medium. The method comprises the following steps: acquiring sequence points in a time sequence; obtaining afirst determination result of whether the sequence point is an abnormal point or not through a pre-constructed statistical model, and obtaining a second determination result of whether the sequence point is an abnormal point or not through a pre-constructed unsupervised learning model; if the first determination result is consistent with the second determination result, taking the sequence pointdetermined as a normal point as a normal sample, and taking the sequence point determined as an abnormal point as an abnormal sample; and obtaining a detection result of each sequence point in the time sequence through the classification model, and marking abnormal points in the time sequence according to the detection result. According to the technical scheme provided by the embodiment of the invention, the problems of missed detection and false detection when a single statistical model or an unsupervised learning model is adopted to detect the sequence points in the time sequence are avoided, and the accuracy and reliability of marking the abnormal points in the time sequence are improved.

The invention discloses a frequency offset estimation method and device. The method comprises the steps of converting local pilot data from a frequency domain to a time domain, and carrying out correlation operation on pilot data of the time domain obtained through pre-calculation and the local pilot data, thereby obtaining a phase sequence; determining the number of sequence points at which a phase is inverted according to a maximum time advance degree Ta estimation value in a current time slot, wherein the Ta estimation value comprises at least one of the Ta estimation value obtained through pre-calculation and effectively maintained history Ta estimation values; and reconstructing the phase sequence according to the number of the sequence points and carrying out frequency offset estimation on the reconstructed phase sequence. Through application of the method and the device, the frequency offset estimation is realized well; the system performance is improved; and the problem that in the prior art, OFDM (Orthogonal Frequency Division Multiplexing) synchronization in an LTE (Long Term Evolution) system cannot be solved well, in particular, the problem that accurate frequency offset estimation cannot be carried out on a single pilot symbol under the condition of frequency hopping and high time offset, is solved,

The invention discloses a method capable of progressively transmitting for storing and accessing aggregated vector data, wherein vector data can be taken as a sequence point set; the sequence point set is used as a basis; the vector data are decomposed into initial data and a series of variable sets; and a formalization model capable of progressively transmitting for storing and accessing aggregated vector data is formed. In the method disclosed by the invention, a vector data aggregation relation model storage scheme is designed under a progressive transmission model; the progressive increment data belonging to one aggregation are stored into a record according to an accuracy level and a mark sequence; the record number of geometric data tables is compressed; and multiple geometric objects are simultaneously stored in one record, thereby enhancing the reading / writing speed of a magnetic disk. Finally, the client cache of the vector data aggregations under the progressive transmissionmodel and hierarchical scheduling strategies based on a visual range are analyzed.

Arrangements described herein relate to inserting implicit sequence points into computer program code to support debug operations. Optimization of the computer program code can be performed during compilation of the computer program code and, during the optimization, implicit sequence points can be inserted into the computer program code. The implicit sequence points can be configured to provide virtual reads of symbols contained in the computer program code when the implicit sequence points are reached during execution of the computer program code during a debug operation performed on the computer program code after the computer program code is optimized and compiled.

The invention discloses a metering system secondary circuit monitoring method and device based on fundamental wave zero sequence characteristics. The method comprises the steps as follows: acquiring three-phase voltage in a voltage circuit of a high-voltage metering system, three-phase current in a current circuit and neutral current; obtaining a zero sequence voltage component and a zero sequencecurrent component through vector superposition; extracting amplitude and phase of a fundamental wave zero sequence component; establishing a classifier based in the depth belief network with amplitude and phase of fundamental wave voltage, amplitude and phase of fundamental zero sequence point current and the absolute value of the difference between the fundamental wave zero sequence current andneutral current as input variables and various faults as output variables to realize classification and recognition of faults. Secondary circuit fault characteristics of the high-voltage metering system can be extracted accurately, various faults can be classified and recognized accurately, so that faults are effectively eliminated, secondary circuits are monitored in real time, and the safety, stability and accuracy of electric energy metering are guaranteed.

The invention relates to a trajectory similarity calculation method based on interpolation and integration. The trajectory similarity calculation method comprises the following steps: 1) mapping trajectory sequence points to a large space with the same measurement based on a complete bijection function; 2) performing interpolation fitting on the mapped track sequence points by using a Lagrangian interpolation function to obtain a fitting curve; and 3) on the basis of the two contents, calculating similar attributes of the track sequence by applying an integration method. The method has the beneficial effects that the problems of low accuracy of a traditional point matching algorithm, weak resistance to the non-uniform sampling rate of noise and the efficiency of a deep learning algorithm are solved. A method of combining Lagrangian interpolation with integration is provided, a dynamic calculation method of a point matching algorithm is abandoned, and a static calculation method is adopted. A similarity attribute is defined, the similarity attribute is embedded into each trajectory, the similarity of any two trajectories is prevented from being repeatedly calculated, and the time complexity of similarity calculation is greatly reduced.

The invention discloses a method for extracting a quadratic surface from a three-dimensional point cloud. The method comprises the following steps: firstly, fitting a curved surface corresponding to each point by utilizing a K neighborhood point set of each point, and calculating a curved surface parameter standard deviation corresponding to each point; arranging the point sets according to the sequence of the curved surface parameter standard deviations from small to large; sequentially taking out each point from the sequenced point set, and when the curved surface parameter standard corresponding to the taken-out point is smaller than a set threshold value and is not marked as a growing point, regarding the point as an initial seed point; carrying out region growth from the initial seedpoint, marking the growth point belonging to the curved surface by using the serial number of the current region, and carrying out dynamic fitting on the characteristic parameters of the curved surface until the growth of one curved surface is finished; and repeating the steps to take out the points from the point set and carry out dynamic fitting until the curved surface parameter standard deviation is greater than the threshold value, and finally extracting the corresponding curved surface according to the mark serial number in the point cloud. According to the method, the quadratic surfacecan be quickly and accurately extracted from the three-dimensional point cloud, and the optimal surface parameters are obtained.

The invention relates to a method and device for predicting disease end point events, an electronic device and a computer readable medium. The method includes steps that the information at a disease occurrence and diagnosis and treatment stage is collected as the T0 sequence point feature; the information of each review is collected as the Ti sequence point feature of the corresponding review; a deep learning neural network model is utilized to predict a disease end point event in a future time window, in a DNN model of the deep learning neural network model, corresponding to each sequence point, one of the T0 sequence point feature to the Ti sequence point feature is respectively received, and a multidimensional vector is outputted; the multi-dimensional vector outputted by the DNN modelof each sequence point is received by a sequence neural network model of the deep learning neural network model; input from the sequence neural network model is received by an output layer of the deeplearning neural network model, and the output result is generated. The method is advantaged in that prediction accuracy can be improved.

The invention discloses a self-adaptive agent model optimization method based on a complex form and an application of the self-adaptive agent model optimization method in battery module optimization design. Due to the fact that a traditional optimization method is high in cost, long in period and complex in operation when solving a black box problem or an engineering problem with a complex performance function, the self-adaptive agent model optimization method based on the complex form is provided and applied to optimization design of a battery module. The method comprises the following steps:firstly, constructing an ANSYS geometric optimization model of the air cooling battery module; secondly, performing CFD calculation according to the ANSYS geometric optimization model; then, establishing an agent model by utilizing a test design method and an approximation technology, and finally, optimizing the air cooling battery module by the self-adaptive agent model optimization method basedon the complex form. The complex form method is applied to sequence point-adding iteration of the agent model. Compared with a traditional sequence point-adding optimization method, the method has the advantages of being few in added samples, high in convergence speed, high in local precision, high in optimization efficiency and the like, and the wide application prospect is achieved.

The invention discloses a parallel computing global optimization algorithm based on a Kriging agent model, namely a PEI-R algorithm, and belongs to the technical field of global optimization algorithms. According to the method, the agent model method is matched with the parallel point adding criterion, so that the efficient and high-precision global optimization calculation is achieved. A main sample and a local sampling strategy are selected through a P-EI criterion to increase the calculation efficiency of the algorithm so as to design a domain reduction strategy to improve the precision ofthe algorithm. According to the method, the efficient parallel computing can be achieved through the multi-core parallel capacity of a computer, the efficiency can be improved by three times comparedwith a traditional EI sequence point adding criterion, and the precision is improved by at least one order of magnitude. The method is good in universality and few in calculation times of the target function, not only is suitable for a conventional optimization problem, but also is suitable for solving the complex engineering and multidisciplinary optimization problems which cannot obtain gradients.

The invention discloses a fast fourier transform circuit which is used for a fast fourier transform of variable-length sequence points, and the circuit comprises a mixed-base operation module, a base combination selection module and a control module, wherein the mixed-base operation module comprises a plurality of base operation units with different base numbers; the base combination selection module selects a combination of the base operation unit according to the number of points of a sequence to be operated; and the fast fourier transform is carried out on the sequence points by utilizing the selected base operation units through the control module. The base operation unit adopted in the invention is variable and selectable, namely the fast fourier transform is carried out on 2n point by a mixed base, and the high-speed low-time delay fast fourier transform circuit is implemented by utilizing relative lower hardware cost. The fast fourier transform circuit has great flexibility, and can perform variable-length fast fourier transform (FFT) operation.

The invention discloses an ultra low sidelobe pulse transformer design method of a linear frequency modulation pulse signal. The method is characterized in that the linear frequency modulation signal which needs to be processed is sampled as a time interval T so as to acquire a M point sampling sequence; a sampling sequence point number is taken as a an initial point number N of a pulse pressure filter, wherein the N equals to the M; a sidelobe peak value of sampling sequence pulse pressure processing is taken as a target function and a signal to noise ratio loss and main lobe widening are taken as a limitation condition so as to establish a convex optimization model and solve, and acquire a group of pulse pressure filter coefficients; the pulse pressure filter coefficients are solved so as to acquire a corresponding pulse pressure sidelobe peak level; if the sidelobe peak level does not reach a practical application requirement, a pulse pressure filter order is N+1, the convex optimization model is rebuilt and solving is performed; if the sidelobe peak level reaches the application requirement, the pulse pressure filter coefficients, a lowest order and a peak sidelobe level after pulse pressure processing are output. By using the method in the invention, ultra low sidelobe pulse compression processing of the linear frequency modulation signal is realized; a low sidelobe level can be acquired and the order of the pulse pressure filter is flexible.

The invention provides a method and system for establishing a three-dimensional dynamic model of a power transmission line tower subjected to external force deformation. The method comprises the steps of reading original tower joint data, assuming that two joints of the tower are connected through a framework, constructing a framework of the tower according to the tower joint data, transforming the abstract frameworks into tower materials with solid shapes to obtain corresponding three-dimensional model data, calculating new coordinates of a new stress joint of a current time sequence point under deflection through a universal mechanical model according to external force to obtain new tower joint data, continuing to draw a new framework corresponding to a next time sequence point and obtain new tower three-dimensional model data till the tower three-dimensional model data corresponding to all the time sequence points are obtained, loading the tower three-dimensional model data to a universal three-dimensional geographic information platform, and playing the animation of the stress conditions of the tower according to the time sequence.