649results about How to "Reduce space complexity" patented technology

The invention provides an incremental data acquisition method and an incremental data acquisition system; wherein, the method comprises that: a relational database snapshot list corresponding to a target list is created according to the structure information of the target list; extraction of snapshots in the target list with time points appointed is completed with the created snapshot list; and snapshot intercomparison is performed according to the snapshots with different time points so as to capture incremental data. The invention has the advantages that the snapshot list is adopted to store snapshots, and maintenance of metadata information of the incremental data is not needed, thus versatility is enhanced; furthermore, intercomparison time of snapshot record is shortened, computer system computation is decreased, and computer system resources are saved through creating the cluster index of the snapshot list.

The invention discloses a low-complexity polarization code decryption SCL algorithm based on segmented verification assistance, and the algorithm selects a parity check code, repeatedly uses the parity check code in a decryption process, and achieves the performances of SCL-CRC24. Moreover, compared with a conventional scheme, the algorithm is better in low signal to noise ratio anti-noise performance and error rate. In addition, the spatial complexity of the algorithm is lower than that of the SCL-CRC24, the time complexity is greatly reduced, and the decoding speed is greatly improved. Compared with a CRC-24 verification algorithm sacrificing multiple information bits, the algorithm employs a parity check method, enables verification elements to be distributed in the information bits, is repeatedly used in the decoding process, and is lower in time complexity than the prior art.

The invention discloses an online lithium ion battery residual life predicting method based on relevance vector regression, belongs to the technical field of lithium ion battery life prediction, and solves the problem that the residual life of the existing lithium ion battery is predicted by an offline method with low precision. The method comprises the following steps: firstly selecting original samples, performing phase-space reconstruction to construct a training sample set; initializing the model parameters of RVM (relevance vector machine); performing RVM training to obtain a RVM prediction model; comparing the obtained prediction value with ynew, if yes, the constructed novel training set WS equal to WSUINS, retraining RVM, and updating the RVM prediction model; otherwise, keeping the RVM prediction model stable; performing recurrence prediction until the prediction value is smaller than the invalid threshold value U, and finishing the online prediction of the residual life of the predicted lithium ion battery. The method is suitable for prediction of the lithium ion battery residual life.

The invention discloses a non-overlapping horizon cascade-type multi-camera relay tracing method and a system, and belongs to the technical field of visual surveillance. The method comprises the following steps of building a layered real-time network hardware surveillance system and building a monitoring sub network and global scene map mapping, carrying out abstract mathematical modeling on the map mapping to obtain a corresponding topological node connection diagram, initializing the tracing information and starting tracing, adopting a single-target tracing strategy based on scale invariant features and particle filtering in a single camera view field, adopting layered searching and a cascade tracing strategy and adopting federated data association algorithm in the topological sub network and adopting temporal and spatial association algorithm in searching in the global topological map, and judging termination and loss of target tracing and terminating the tracing. The method relies on the prior video surveillance network in the industry, a suspicious target can be traced in a scene crossing mode, the system adopts the distributed-type layered searching method, the tracing cost is reduced, and the suspicious target can be traced in real time.

The invention relates to a visual navigation based multi-crop row detection method, which belongs to the related field of machine vision navigation and image processing, and aims to quickly and accurately extract a plurality of ridge lines in farmland and meet the requirements of the real-time navigation and positioning of agricultural machinery. The invention provides an agricultural machine vision navigation based multi-crop row detection method, which comprises the steps: calibrating camera parameters, acquiring video and image frames, and carrying out distortion correction for the image; dividing a crop ridge line area, extracting navigation positioning points by using the vertical projection method, and calculating the world coordinates of the positioning points; using the random straight line detection method to calculate the positioning points, and detecting the straight lines on which crop ridge rows are positioned; and obtaining the position of each crop ridge row in a world coordinate system relative to the agricultural operation machinery by calculation according to the slope parameters and intercept parameters of the straight lines. Compared with the traditional technology, the technical scheme of the invention greatly reduces time complexity and space complexity, and also improves the accuracy and the real-time of navigation.

The present invention discloses a method for business dispatching in a time triggering FC network, and relates to the field of an FC network. The method comprises the following steps of: establishinga network model, calculating a cluster period, and determining the length of a single time slot of each time triggering message; determining the priority of a TT message according to a certain rule; planning a link transmitting the TT message; detecting the schedulability of the TT message; selecting the TT message with the highest priority to arrange the time slot of the TT message; according tothe periodicity and the transmission link of the TT message, arranging all other time slots; arranging the TT message of the next priority, and solving a time slot map meeting conflict-free and periodsending of all the TT messages in all the links; and according to a whole network and total business time slot map, solving the sending and receiving time dispatching tables in each terminal and eachexchange. The method ensures the transmitting and receiving of the message determinacy in the optical fiber channel network so as to meet the demand of real-time message dispatching in the complex application system and allow the upper-layer application system performance to be more determined and reliable.

The invention discloses an IRS-based UE position determination method, a communication method and a system. The method comprises: selecting a preset number of reflection unit sets on an IRS, and activating each set according to a preset time sequence; after each set is activated, emitting electromagnetic signals to the set are reflected, wherein each activated set selects different code words according to a preset time sequence so as to reflect received electromagnetic signals according to different reflection directions; according to the intensity of the electromagnetic signal reflected by each set under each code word at the receiving end, determining the code word when the intensity of the reflected electromagnetic signal received by the receiving end is maximum, and determining the channel time delay under the code word, so as to determine the distance between each set and the UE according to the channel time delay; estimating the position of the UE according to the position of each set on the IRS and the distance between each set and the UE; and determining a reflection coefficient matrix or vector of the IRS according to the position of the UE, the IRS and the AP position, thereby realizing effective communication between the wireless AP based on the IRS and the UE. According to the invention, effective communication of the AP-IRS-UE channel is realized.

The invention relates to an electrocardiogram signal sparse decompression and compression system based on a concise common dictionary base. The electrocardiogram signal sparse decompression and compression system based on the concise common dictionary base comprises a concise common dictionary base offline training module, an electrocardiogram signal online compression module and an electrocardiogram signal reconstruction module, wherein the electrocardiogram signal online compression module is connected with the electrocardiogram signal reconstruction module. The concise common dictionary base offline training module is used for integrating multisource electrocardiogram signal training samples offline to construct a common training sample set, segmenting sample signals, discretizing a Gabor function to form a super complete Gabor dictionary, sparsely decomposing the segmented signals by the Gabor dictionary to obtain a primary common dictionary base, and simplifying the dictionary by clustering algorithm to obtain a concise common dictionary base. Based on the concise common dictionary base, the electrocardiogram signal online compression module is used for sparely decomposing the signals. Based on the concise common dictionary base, signal segments of the electrocardiogram signals are reconstructed to restore complete signals and display signal waveform. The electrocardiogram signal sparse decompression and compression system based on the concise common dictionary base is suitable for implementation on embedded or mobile hardware platforms with resources limited.

The invention relates to a fisheye lens image distortion correction method based on an orthogonal projection, which comprises the following steps: 1) using a fisheye camera to take a picture, that is,a fisheye image; 2) performing distortion correction on the fisheye image: obtaining the radius and center point of the fisheye image according to the geometrical characteristics of the fisheye image; using an orthogonal projection to transfer the fisheye image into a hemispherical surface; using lateral and longitude curves to carry out mesh division on the hemispherical surface, thereby transferring into lateral and longitude coordinate values of the hemispherical surface; finally, projecting the lateral and longitude coordinate values to a target image coordinate to realize coarse correction conversion of the fisheye image; after using the orthogonal projection to carry out coarse correction on the fisheye image, using a plurality of angular points of the distorted checker image and the target image to carry out affine transformation; then, using a look-up table to save a coordinate mapping relation table from the fisheye image to the correction image; and using the look-up table to achieve accurate correction of the fisheye image in the checkerboard region. The method in the invention is stable in performance, safe and reliable.

The invention discloses a dark channel prior based image defogging method which includes the steps of 1, dividing the image I(x) on the basis of the classical clustering algorithm to acquire a candidate sky region It(x); 2, corroding the candidate sky region It(x) to acquire sky brightness; 3, performing mini-value filtering on the image to improve the same according to the sky brightness so as to acquire a coarse-estimation transmissivity image; 4, optimizing the coarse-estimation transmissivity image by means of guide filtering to acquire a transmissivity image; and 5, acquiring a recovered image based on an atmospheric scattering model. The dark channel prior based image defogging method has the advantages of processing airglow more reasonably, reducing image block effect, improving overall brightness of images and making the images more natural.

Systems and methods are disclosed for a server learning new words generated by user client devices in a crowdsourced manner while maintaining local differential privacy of client devices. A client device can determine that a word typed on the client device is a new word that is not contained in a dictionary or asset catalog on the client device. New words can be grouped in classifications such as entertainment, health, finance, etc. A differential privacy system on the client device can comprise a privacy budget for each classification of new words. If there is privacy budget available for the classification, then one or more new terms in a classification can be sent to new term learning server, and the privacy budget for the classification reduced. The privacy budget can be periodically replenished.

The invention discloses a segmentation polarization code coding and decoding method and system based on LSC-CRC decoding. The method comprises steps of combining and separating a plurality of independent channels to obtain bit channels as many as the independent channels, obtaining the capacity of each bit channel, and obtaining the number of the fully polarized bit channels; dividing the free information bit sequence to be transmitted into the corresponding number of sub-sequences according to the number of fully polarized bit channels, subjecting each sub-sequence to polarization code decoding, and transmitting the encoded information to the corresponding bit channel; and after a receiving end receives the encoded information, performing segmentation decoding according to the LSC-CRC decoding algorithm, and finally connecting the obtained decoded sub-sequences in an end-to-end manner to obtain the decoding sequence. The channel coding and decoding method is simple to operate, the coding and decoding space complexity is reduced, and the decoding accuracy is improved.

The invention discloses an unmanned aerial vehicle visual detection method for high-voltage line insulators. The method comprises the following steps of: obtaining a high-voltage line insulator image; converting the high-voltage line insulator image from an RGB model to an HSV model; detecting a brightness component of the HSV model by adoption of a cross gradient search method, and obtaining a direction gradient and a spatial brightness similarity so as to generate a foreground image; carrying out connected domain segmentation on the foreground image by adoption of a 8-neighborhood connected domain segmentation method so as to obtain an insulator connected domain image; carrying out edge extraction on the insulation connected domain image by adoption of an LOG operator so as to obtain edge information of the image; carrying out 8-neighborhood edge classification on an image edge point by adoption of a 8-neighborhood edge tracking method; for pixel class groups obtained through the 8-neighborhood edge classification, carrying out edge linear detection on the groups, and displaying a recognized insulator profile. According to the method, complete insulator connected domain images can be obtained, so that the insulation recognition correctness is effectively improved, the operation speed is effectively improved and the calculation complexity is reduced.

The invention discloses an image super resolution (SR) reconstruction method based on subspace projection and neighborhood embedding. The method is characterized by: using first and secondary subspace projection methods to project original high-dimensional data to a low-dimensional space, using dimension reduction feature vectors to show a feature of a low-resolution image block so that global structure information and local structure information of original data can be maintained; comparing a Euclidean distance between the dimension reduction feature vectors in the low-dimensional space, finding a neighborhood block which is most matched with the low-resolution image block to be reconstructed, using a similarity and a scale factor between the feature vectors to construct an accurate embedded weight coefficient so that a searching speed and matching precision can be increased; then constructing the similarity and the scale factor between the feature vectors, calculating the accurate weight coefficient and acquiring more high frequency information from a training database; finally, according to the weight coefficient and the neighborhood block, estimating the high-resolution image block with high precision, reconstructing the image which has the high similarity with a real object, which is good for later-stage real object identification processing.

The invention relates to a wind farm multi-model draught fan optimized arrangement method based on a genetic algorithm. The method includes the following steps that (1) a wind farm region is divided into square meshes which are the same in size according to the diameter of a draught fan, and an integer matrix which is the same in line and row is generated randomly to be used as the initial solution of the algorithm; (2) the individual fitness value of a current generation is calculated; (3) parent individuals participating in crossover are selected through even random selection operators, and then filial generation individuals are generated by the adoption of improved crossover and mutation operators; (4) repairing operators are introduced to the individuals in a population; (5) a Tabu operator is introduced to an optimal solution of the current generation of the population, the optimal solution is used as the initial solution of a Tabu algorithm, and the neighborhood solution of the optimal solution is searched for; (6) whether the biggest number of iterations is reached or not is judged, if yes, the multi-model draught fan optimized arrangement is completed, and if not, the step (2) is executed again. Compared with the prior art, the wind farm multi-model draught fan optimized arrangement method based on the genetic algorithm has the advantages of being visual in coding mode, good in performance index, high in local search capacity, high in expansibility, high in practicability and the like.