485results about How to "Reduce computational difficulty" patented technology

The invention relates to a method for controlling an index time-varying slide mode of flexible spacecraft characteristic shaft attitude maneuver, and belongs to the technical field of spacecraft control. The method comprises the steps that firstly, a system dynamically equivalent model, a dynamic model and a flexible vibration model are established under a spacecraft system, then, the vibration frequency and the damping ratio parameter of a closed loop system with the index time-varying slide mode control law are calculated, and a single-shaft multi-modality filtering input shaping device with a characteristic shaft as a rotary shaft is designed according to the designing method of the single-shaft input shaping device to restrain flexible vibration in three-shaft motion. Meanwhile, a state observer is designed to estimate flexible modal information in real time, and the method for controlling an output feedback index time-varying slide mode is formed. At last, saturability analysis is conducted on control torque so as to satisfy the physical saturation constraint of the control torque. By means of the method, the application range of existing input shaping is expanded, the input shaping technology is expanded from single-shaft maneuver to three-shaft maneuver, the self-robustness of filter input shaping is enhanced, and the purpose that the attitude maneuver path of the spacecraft is the shortest is achieved.

The invention discloses a traffic detection system based on millimeter wave radar and video, and belongs to the technical field of data acquisition and processing in intelligent transportation. According to the traffic detection system based on the millimeter wave radar and the video, target information is collected through a millimeter wave radar sensor and a video sensor, world coordinates are converted into image plane coordinates, the position of a target projection collected and detected by the millimeter wave radar sensor on a image plane is determined, the target type is learned and recognized by an image machine, the data collected by the video sensor and the millimeter wave radar are fused, and the speed, coordinates and type of a target are output. According to the traffic detection system based on the millimeter wave radar and the video, the data calculation difficulty of the system is reduced and the system flow is simplified. The data detected by the video sensor and the millimeter wave radar are subjected to data fusion in real time, and the fused target information is sent to a system platform, the calculation amount of the system is reduced, the response time of thesystem is accelerated, and the detection precision is improved.

The invention discloses a monocular visual error measurement system for a cooperative target and an error limit quantification method. The monocular visual error measurement system is specifically characterized in that visual marker points are formed in the outer surface of the cooperative target, a calibration target adopts a black and white checkerboard like pattern and is used for the intrinsic and extrinsic parameter calibration of a camera, the camera is used for acquiring the images of the visual marker points and the images of the calibration target in one frame and transmitting the images to the computer, a first theodolite and a second theodolite are used for observing the calibration target to obtain an observation value A, observing the visual markers to obtain an observation value B and transmitting the observation value A and the observation value B to a computer, and the computer is used for receiving the calibration target image and marker image acquired by the camera, the observation value A and the observation value B, computing the camera pose measurement value and the real pose value of the cooperative target relative to the camera and computing a measurement error. By adopting the error limit quantification method, the measurement error can be quantified and decomposed so that each key parameter index is in the error limit.

The invention relates to an implementation method of a streaming media quality monitoring report based on user experience interaction. The implementation method comprises the steps that: a user-defined two-way-transmission experience quality QoE interaction protocol and relative network environment parameters and business performance parameters are firstly set; a server monitors the streaming media transmission state; a client monitors the streaming media receiving state and estimates the user experience quality; an S-C (server-client) report and a (client-server) report are respectively generated and are transmitted through a network; and the real-time interaction of streaming media quality monitoring reports is realized between the client and the server. In the invention, according to the base of the existing network technology, the multi latest results of the streaming media quality monitoring and monitoring technology are widely absorbed, and the method is comprehensively provided. The method disclosed by the invention has the advantages that the operation steps are simple, the occupied bandwidth resources are few, the computing difficulty is low, the existing network does not need be updated and reformed, and the implementation is easy, the method has an important significance to the operation and management of the streaming media in the existing network, and has a good population and application prospect.

The invention relates to an aviation geophysic magnetic type exploration data processing method. The method is characterized in that the baseline direction unit vectors and sensor plane normal vectors, corresponding to an inertia navigation coordinate system, and the sensor plane normal vectors, corresponding to a three-component magnetic instrument coordinate system, of five plane superconductive magnetic gradient sensors can be accurately obtained, and then the premise is provided for accurately obtaining five independent components of a full-tensor magnetic gradient corresponding to a geographic coordinate system; the five independent components of the full-tensor magnetic gradient are calculated by a coordinate system conversion method, the middle process of calculating the attitude angles, corresponding to the coordinate system, of the five plane superconductive magnetic gradient sensors is not needed, the inertial navigation coordinate system is used as the coordinate system of the measurement system, and the attitude data measured by inertial navigation are converted by the one-time coordinate system, so as to obtain the five independent components of the full-tensor magnetic gradient corresponding to the geographic coordinate system. The method has the advantages that the calculation difficulty is decreased, the calculation efficiency is improved, and the method is more suitable for measuring the attitude time varying of measuring platforms, such as aviation magnetic measuring.

In a planning model, a decision variable optimization process (200) generates a planning function (122) describing the planning model, the planning function (122) depending upon a set of decision variables (125). The planning function (122) is separated into independent planning functions, SPi, each of which depend upon different decision variables (125). Each of the independent planning functions, SPi, is independently optimized to obtain decisions for the different decision variables (125), and an outcome is presented that indicates the decisions. The planning function (122) further includes an embedded constraint function that introduces an embedded constraint to weaken the coupling between decision variables (125) in the planning model, thereby reducing an N-dimensional optimization problem into a lower order optimization problem.

The present invention relates to an analysis and prediction method for dynamic performances of a rubber material structure, and particularly to a step-by-step analysis and prediction method for the dynamic performances of the rubber material structure. The step-by-step analysis and prediction method is used for performing finite element analysis and prediction of the high-frequency dynamic performances on the rubber material structure. The method comprises the following test and prediction steps: step one, fitting a super-elastic constitutive relation of the rubber material; step two, performing a viscoelasticity property test on the rubber material under different strain amplitudes; step three, fitting a viscosity constitutive relation of the rubber material; and step four, analyzing and predicating the dynamic performances of the rubber material structure. A calculation result is a final result, without the need of superposition of the calculation result, thereby reducing the computational difficulty and shortening the solution time; and an actual modeling and analysis process is more simple, clear, and easy to understand and operate, and has higher prediction accuracy, so as to meet the requirements of engineering analysis.

The invention provides a reconfiguration method for a compression sensing signal, which comprises the following steps: A) calculating an inner product (g1=phi Ty) of a signal y subjected to compression sensing treatment and each row of a sensing matrix phi, and taking the inner product as an inner product result of first iteration; B) judging if stopping iteration according to the inner product result gt of the iteration; if not, searching an index value lambda t corresponding to an element with the maximum absolute value from the inner product result gt of the iteration, adding the index value lambda t into an index set, calculating the inner product of the next iteration and starting the next iteration process, and returning to the step B, wherein t is the iteration index value and is the No. lambda t row of the matrix X=phi T phi; and if stopping, forming a matrix phi lambda by rows of the sensing matrix corresponding to different index values in the present index set, and reconfiguring the compression sensing signal according to the formed matrix phi lambda and the signal y, wherein the rows in the matrix phi lambda are arrayed according to the sequence of the index values from low to high, and lambda is the set composed of different index values in the present index set. According to the reconfiguration method provided by the invention, the calculating time and resource are saved.

The invention discloses a measurement method for determining a position of a crane hook, which comprises the following steps of: 1, during the filling, ensuring that a folding cylinder only takes a working condition, locking a piston rod of the folding cylinder firmly after extending to the farthest place, finally enabling a folding arm, the folding cylinder and a telescopic arm to form a rigid body; 2, establishing a sphere coordinate system with a hinge point center of the folding arm and a rotary table as a coordinate origin O, wherein the connecting line of the coordinate origin O and thecenter point C of a fixed pulley of the crane hook is a coordinate radius phi, and regulating the telescopic direction of the telescopic arm to ensure that the telescopic arm is parallel to the coordinate radius phi, wherein the state is an initial zero state of an ejector arm of the crane; and 3, during the work, always ensuring that the telescopic direction of the telescopic arm is parallel to the coordinate radius phi, measuring the length variable value delta L of the telescopic arm, the length variable value delta h of a steel rope, the amplitude angle variable value delta alpha of the folding arm and the rotary angle theta of the rotary table by using a sensor to obtain the position of the crane hook. The invention reduces the parameters required for determining the position.

This invention relates to an up link data packet transmission method of an Ethernet passive light network, in which, an ONU process includes: judging if a data packet on a logic channel is needed to be split and if the logic channel is at the slice state and generating an intermediate slice data packet, a head slice data packet, a tail slice data packet or a complete data packet data packet, the OLT process includes: judging if the logic channel buffer storage is at the slice state, if the data packet is a complete packet and receiving the complete and incomplete data packets of the slice state, the complete and incomplete data packets of non-slice state to realize the maximum usability of links.

The invention discloses a cable fault detection and analysis method. According to the method, an impedance frequency spectrum and a phase frequency spectrum of a cable are taken as basis, subsection characteristic impedance on an impedance frequency spectrum attenuation trend curve is calculated with a subsection interception method, an equation of equivalent impedance is established, R, L, G and C parameters of cable transmission impedance are calculated, a transmission impedance model based on R, L, G and C parameters is obtained, an error distance graph with a cable distance length serving as a variable is obtained through error calculation and comparison of the transmission impedance model and the tested impedance frequency spectrum and phase frequency spectrum, finally, local zero points on the error distance graph are analyzed, and fault detection and fault type identification are realized. Compared with the prior art, on the basis of a relative signal transmission rate calculation method with low calculation difficulty and high calculation accuracy, accurate fault positioning and multi-point fault positioning can be realized, and the fault type identification can be realized.

The invention discloses an electronic nose feature selection optimization method on the basis of multiple Fisher kernel discriminant analysis. The electronic nose feature selection optimization method comprises the following steps: firstly, acquiring a sample feature matrix; initializing parameters and establishing a fundamental kernel function according to the parameters; then calculating a composite kernel matrix on the basis of a fundamental kernel matrix, calculating a projection of the composite kernel matrix in a high-position feature space, then feeding the projection into a classifier to carry out mode identification to determine a kernel function with the highest identification rate; finally, on the basis of the kernel function, calculating a projection of a new sample matrix in the feature space, using the projection as an electronic nose signal and using the electronic nose signal as an input of the classifier to carry out mode identification. The electronic nose feature selection optimization method has the obvious effects of solving the problem of poor data discrimination after high-dimension projection is implemented by a single kernel function method, solving the problem of redundancies between sensors, optimizing a sensor array, reducing data dimensions and improving the identification rate of the electronic nose signal so as to provide beneficial guide for a doctor to select a suitable treatment method.

The invention discloses a system evaluation and detection method by a Bayesian model. The method includes: step A, establishing a logic relationship and an event relationship between a software system and a database therein after variable and relationship conversion; step B, establishing a fault tree model for a logic model according to the step A; step C, establishing a Bayesian network based on the fault tree model; step D, conducting system evaluation and detection based on the Bayesian network. The system evaluation and detection method by the Bayesian model has the advantages of low computational complexity, low computational difficulty, simplicity and practicality when used for system evaluation and detection by the Bayesian model.

The embodiment of the invention relates to the field of communication, and discloses a robot path planning method, a robot, electronic equipment and a storage medium. The method comprises the following steps: acquiring a target point of a robot in an artificial potential field grid map that is formed by superposing a basic grid map generated according to a local map and an obstacle cost map generated according to an obstacle; acquiring a plurality of alternative pose points of the robot after the preset duration, and determining a target pose point according to a path cost of each pose point to the target point, setting the target pose point to be the pose point with the minimum path cost; and generating a target path according to the state information of the target pose point. The path planning is carried out in the artificial potential field grid map, so that the situation that the path planning cannot be carried out because a grid map cannot be generated when a target point is on anobstacle is avoided, and the path planning efficiency and effect are improved; and path planning is carried out according to the pose point with the minimum path cost to ensure that the obtained pathis the optimal path.

The invention discloses a face authentication method and device and belongs to the field of image processing and mode identification. The method comprises the steps of: obtaining face image sample pairs; carrying out blocking on the obtained face image sample pairs; calculating local gray scale characteristic vectors and local direction gradient histogram HOG vectors of obtained blocks; and according to the calculated local gray scale characteristic vectors and local direction gradient histogram HOG vectors, calculating and judging whether the face image sample pairs belong to one person. By adopting the face authentication method and device, the interference of factors such as illumination, expression and age is effectively avoided, and simultaneously, the accuracy of face authentication is substantially improved.

The invention relates to a money checking method and system. The method comprises the following steps: converting a UV image of paper money into a binary image; inquiring a maximum value position column I in binary image column projection, and substituting first pixels in the maximum value position column I with second pixels; circularly inquiring a maximum value position column II in the binary image column projection within a preset inquiring frequency threshold value, and substituting first pixels in the maximum value position column II with second pixels if the quantity of the first pixels is greater than a quantity threshold value, wherein the maximum value position column I is a position column with the projection in a magnetic safety line set zone line being a maximum value; the maximum value position column II is a position column with the projection within preset zones on the two sides of the maximum value position column I being a maximum value. By locking possible zones of a magnetic safety line, the system reduces calculated amount, reduces calculation difficulty and the error rate, solves the problem of the interference of splicing traces, and improves the accuracy.

The invention discloses a method for detaching products based on a connected piece level network diagram, aiming to solve the problems of effectively recycling waste and old materials to reduce the waste of the materials, and solving the problems of energy consumption, pollution and the like caused by the production of raw materials. The method comprises the following steps of: extracting / inputting attribute information of parts, extracting / inputting assembly information of the products, building and detaching models, generating detaching sequences and optimizing the detaching sequence. In the invention, the connected piece level network diagram is used as the detaching model, and an adjacent matrix is utilized to represent the adjacent relationship between nodes. The node of the model only represents the connected parts, not all parts, thereby effectively reducing the number of the nodes and edges in the diagram, reducing the dimensionality of the adjacent matrix, reducing the calculation difficulty and improving the processing speed. The detaching sequence of the product is generated based on a method of constraint removal, so that the obtained detaching sequence has more valuable meaning and maneuverability.

The invention provides a power frequency electric field computing method for a rolling ground overhead transmission line based on a charge simulation method. The method comprises the following steps that a, a mirroring ground is selected, and it assumes that the mirroring ground extends into a rolling ground; b, simulated charges and matched points corresponding to the simulated charges are arranged on a wire and a non-mirroring ground, and the electric potential of the rolling ground is made to be zero; c, on the basis of the superposition principle, a simulated charge equation set is constructed, and the simulated charges are solved according to the simulated charge equation set; d, power frequency electric field distribution of the rolling ground is computed according to the simulated charges. The method is based on the image theory and combined with the simulated charge optimization method, the electric field distribution of the complex terrain where an overhead conductor path passes through can be computed, the technical problem that the electric field distribution of the rolling ground cannot be accurately computed in the traditional method is effectively solved, accuracy of power frequency electric field computation of the conductor path is effectively improved, computation difficulty is greatly lowered, the computation quantity is reduced, computation precision is further improved, and the adaptability of the electric field computation method is enhanced.

The invention discloses a liver cancer postoperative recurrence risk prediction method combining pathological images and clinical information, and belongs to the technical field of cancer postoperative recurrence risk prediction model construction. The method comprises the steps: taking patient clinical information and patient tumor area pathological image features extracted by applying an image processing technology as basic variables, further calculating the interaction between the basic variables as input data, performing the fitting of a survival random forest model, and precisely predicting the survival time of a patient. The result of the embodiment of the invention shows that the cross validation efficacy evaluation index C-index of the model provided by the invention is superior tothe result of prediction by only using pathological image features or clinical information, and the accuracy of liver cancer postoperative recurrence risk prediction is significantly improved; besides, the invention further provides a postoperative recurrence risk classification index, so patients can be divided into a high recurrence risk subgroup and a low recurrence risk subgroup, and a doctorcan be helped to make a targeted treatment scheme for the patient.

The invention discloses a target tracking method and system based on adaptive color characteristics and space-time contexts. The method comprises steps that after a first image of a video sequence is inputted, a rectangle frame is utilized to select and track a target; a target confidence graph of the first image is calculated; the tracking target confidence graph comprises a context prior model and a space context model; a space-time context model of a tth image is updated according to space context model learning; convolution operation for a (t+1) image is carried out according to the acquired space-time context model, a target confidence graph of the (t+1) image is calculated, and the maximial likelihood probability position of the target confidence graph is solved and is taken as the optimum target position; the optimum target position is taken as a new tracking target, steps are repeated according to the target confidence graph of the (t+1) image, and the optimum target position of a (t+2) image is determined; optimum target position determination of all the images is realized.

The invention discloses a complex behavior recognition method. The complex behavior recognition method comprises: acquiring three-dimensional bone joint point information of a target motion by using asensor; pre-processing the joint point information, and normalizing a coordinate system; extracting a motion trajectory of each joint point, projecting the motion trajectory to three two-dimensionalplanes; extracting a motion vector between each two frames and the length and the direction angle thereof, using the k-means algorithm to perform clustering to acquire motion primitives, and performing counting to acquire histograms; calculating the weight of each joint point is calculated to form a descriptor according to the time pyramid, the time information, and values of the clusters of allthe histograms; performing SVM classification to achieve motion recognition. The invention can perform feature extraction and effective represent on the motion bone joint point information, and can improve the accuracy of the motion recognition; all the motion information is completely retained, and the motion reconstruction can be performed; all motion classes are clustered, and motion features of the human are captured globally; low-level features are used, the computational difficulty is lowered, the motion recognition efficiency is improved, and the the real-time requirements of the systemis satisfied.

The invention belongs to the technical field of photoelectric detection, in particular to a distance measuring device and a method thereof. The method comprises the following steps of: assembling a large field by using a 2*3 array of multispectral cameras, obtaining background images and labeling characteristic reference points by using real-time image arrangement, and calculating an object distance by using an image convergence shooting algorithm. Because the invention adopts a large-field angle, observed objects are more easily found, and judging whether the observed objects are the same one is more accurate; and because the characteristic reference points are selected after image arrangement, the data volume of object calculation is smaller, and calculation is faster.

This invention discloses a method for studying Chinese new words and a device, which uses a process module to process the searched engine daily record input via an input module, deletes single Chinese word and inquiry words containing non-Chinese composition and puts the left in order according to the inquiry sequence to set a threshold value and delete the inquiry words with sequence lower than the value. The word-dividing module divides the rest inquiry words taking the present words with the number smaller or equal to 4, if the number is greater than 4, then each time takes 4 words and one from the beginning till the last word, then divides the words based on the four-words method. The filter module arrays the new words according to the appeared frequency, sets new threshold value and deletes the new words lower than the threshold value and outputs the left by an output module.

The invention provides a self-adaptive cruise system and a control method based on vehicle to vehicle communication, pertaining to the technical field of cars with the purpose of improving cruise accuracy. The system comprises a vehicle-mounted controller, a satellite positioning system and a wireless communication module. The satellite positioning system and the wireless communication module are connected with the vehicle-mounted controller. The vehicle-mounted controller is used for calculating the time that a car takes to overtake a front car based on information of the front car and the car. When the calculated time is less than the pre-set threshold value and the distance between two cars is larger than or equal to the safety distance threshold value, the car decelerates and determines to cruise at the constant speed based on the speed of the front car. The method comprises following steps of: A, establishing a communication network; B, determining whether a signal is emitted by a front car or not; C, cruising at the constant speed when no signal is emitted by the front car; D, calculating the time that the car takes to overtake the front one based on information of the front car. When the calculated time is less than the pre-set threshold value, the car decelerates and sends a early warning signal to the front car. The system and the method help raise cruise accuracy and self-adaptation.

The invention discloses a bending failure evaluation method for a corrosion defect contained submarine pipeline structure. The method specifically comprises the following steps: detecting the positionand size of the maximum size corrosion defect of a pipeline; calculating the wave and current load borne by the pipeline according to pipeline detection data, working conditions and environmental conditions, and determining the maximum bending moment position and the maximum bending moment value borne by the tested pipeline finally; deducing the formula of plastic ultimate bending moment for thecorrosion defect contained submarine pipeline, and calculating the plastic ultimate bearing bending moment of the tested pipeline according to the formula; comparing the calculated maximum bending moment with the plastic limit bending moment, and judging whether the tested pipeline fails on the premise of taking into account the safety factor. The method has the beneficial effects that overall bending strength calculation and evaluation can be performed on the pipeline containing the small-range long-axis corrosion defect at any position, the finite element modeling and analysis process is omitted, the calculation difficulty is reduced, calculation efficiency is improved, and the requirement of result precision is also met.

A trajectory clustering method comprises the steps of acquiring a target trajectory set, and the target trajectory set comprises a plurality of trajectories; dividing the tracks in the target track set according to the position data of each track in the target track set to obtain a plurality of target track subsets; respectively calculating the similarity between different tracks in each target track subset; and according to the similarity between different trajectories in each target trajectory subset and a preset similarity threshold, clustering the trajectories in each target trajectory subset to obtain a clustering result. According to the method, the tracks in the target track set are divided into the corresponding different target track subsets according to the position data of the tracks in the target track set. When trajectory clustering is carried out on different target trajectory subsets, other trajectories except the target trajectory subsets do not need to be considered, the trajectory similarity can be quickly calculated, and the discovery overhead of similar trajectories is reduced, so that the overall calculation overhead of trajectory clustering is reduced.

The invention relates to a modeling calculation method for a noise sound field of a transformer substation. The method comprises the following steps: buildinga transformer substation model according to the actual scene and dividing a sound source of the transformer substation model into an outdoor sound source and an indoor sound source; measuring sound pressure level corresponding to the outdoor sound source of the transformer substation model on the actual scene and obtaining sound pressure level of the outdoor sound source; measuring sound pressure level corresponding to the indoor sound source of the transformer substation model on the actual scene, converting the sound pressure level into an equivalent outdoor sound source based on the built transformer substation model and obtaining sound pressure level of the equivalent outdoor sound source; converting the sound pressure level of the outdoor sound source and the sound pressure level of the equivalent outdoor sound source into the acoustic power level of the outdoor sound source and the acoustic power level of the equivalent outdoor sound source; and calculating to obtain noise value of the sound field of the transformer substation based on the acoustic power level of the outdoor sound source and the equivalent outdoor sound source. Compared with the prior art, the modeling calculation method for the noise sound field of the transformer substation has the following advantages of easy calculation, few calculated amount and convenient analyses.

The invention discloses an electronic nose parameter synchronous optimization algorithm based on an improved quantum particle swarm optimization algorithm. The method comprises performing wavelet transformation on obtained original electronic nose data; then performing weighting treatment of wavelet coefficients; through the improved quantum particle swarm optimization algorithm based on a novel local attractor computing manner, finding out a weighting coefficient corresponding to the highest electronic nose identifying rate, and classifier parameters to obtain a characteristic matrix of electronic nose signals; inputting the characteristic matrix into a classifier for mode identification. The electronic nose parameter synchronous optimization algorithm based on the improved quantum particle swarm optimization algorithm has the advantages of enhancing early-stage ergodicity and later-stage local optimizing capacity of particles, improving the capacity of quantum particle swarms in searching for global optimal values, and especially for wound infection detection, improving the identification rate of an electronic nose, thereby selecting appropriate treatment methods for doctors and providing beneficial guidance for promoting quick recovery of wounds.

The invention discloses a point cloud analysis-based multi-vegetation region power transmission corridor hidden danger point rapid extraction method. The method comprises the steps of 1, dividing point cloud data into a plurality of grids; Step 2, filtering the point cloud data in each grid; Step 3, extracting ground points from the point cloud data in each grid; 4, constructing a feature vector of the point cloud data to be classified; 5, constructing a training sample set and designing a classifier based on sparse representation; 6, optimizing the calculation method of the undetermined parameters of the classifier; 7, classifying the point cloud data in each grid; Step 8, searching hidden danger points in the grid according to a classification result; Step 9, combining hidden danger point data in each grid; The problems of complex calculation and long period caused by too many feature vector dimensions and classifier design defects in power transmission line corridor point cloud classification are solved.

The invention relates to a DMP-based robot workspace adaptive walking control system and method. The control system comprises: a DMP centroid track generator which generates a centroid track of a humanoid robot based on DMP training according to a planning target and feedback information; a DMP foot sole track generator which generates a foot sole track of the humanoid robot based on DMP trainingaccording to the planning target and the feedback information; and a joint mapping module which performs inverse kinematic calculation on the centroid track and the foot sole track, and uses a motionengine to map the adaptability of the workspace to a joint space, so as to achieve the adaptive walking control of the humanoid robot. The DMP centroid track generator and the DMP foot sole track generator are obtained based on the example track training study of the robot working space. Compared with the prior art, the system and the method have the advantages of adjusting the gait and body posture in real time, and enhancing the environmental adaptability of the humanoid robot walking.