391results about How to "High computational complexity" patented technology

The invention discloses a video shot detection method based on histogram improvement and a clustering algorithm, and relates to image processing techniques. According to the method, the histogram improvement and the clustering algorithm are adopted to compute an intersection of histograms of two adjacent frames of images, and whether a shot change happens is judged according to histogram similarity; if the shot change happens, secondary detection on a shot boundary of the intersection of the histograms of the two adjacent frames of images is carried out by utilizing interframe gray scale / color difference values, pixel difference value computation on each block is carried out respectively by adopting non-uniform block weighting processing, pixel difference values and preset block frame differential threshold values are compared to obtain identification variables, the identification variable of each block is weighted and summarized, and the weighing and summarizing values and the preset block differential threshold values are compared to carry out shot detection. The video shot detection method improves shot detection accuracy and solves the problems of shot false detection, frame number discontinuity, and the like.

The invention provides methods and devices for stereo encoding and decoding using complex prediction in the frequency domain. In one embodiment, a decoding method, for obtaining an output stereo signal from an input stereo signal encoded by complex prediction coding and comprising first frequency-domain representations of two input channels, comprises the upmixing steps of: (i) computing a second frequency-domain representation of a first input channel; and (ii) computing an output channel on the basis of the first and second frequency-domain representations of the first input channel, the first frequency-domain representation of the second input channel and a complex prediction coefficient. The upmixing can be suspended responsive to control data.

The invention discloses a personal identity identification method based on hand shapes, which adopts an imaging device to obtain human hand images, and obtaining personal character description through computer analyzing and processing, and achieving personal identity identification. The concentrate implementation step comprises the following steps: firstly, adopting an imaging device to obtain hand shape images, secondly, extracting hand shape outlines on the hand shape images, thirdly, extracting hand shape characteristic points according to the hand shape outlines, fourthly, forming hand shape characteristic vectors according to the hand shape characteristic points, fifthly, matching hand shape characteristics according to the hand shape characteristic vectors. The personal identity identification method is mainly characterized in of simple algorithm, high received degree of a tester and stable performance, which is easy to achieve multi-modality identification. The personal identity identification method is particularly suitable for the occasions of a gate inhibition and the like.

The invention provides a criminal identification and forecast method. The method adopts a data pre-processing method in data mining; aiming at criminal information such as data, street address, criminal police zone, week, criminal type, criminal description and sentence processing, attribute reconstruction, feature extraction and feature selection are performed, the correlation between the criminal information is mined, a characteristic factor with maximum difference is generated, and the correlation between the characteristics factor and a criminal result, namely the criminal type is generated; and then a model integrating Gaussian Naive Bayes, a neural network, Logistic regression, regularized regression, K neighbor, random forest, a support vector machine and an XGBoost learning algorithm is built to obtain an element classifier based on a weighted voting classifier having highlight classification and favorable clustering effect, reconstructed data is analyzed, processed and identified, a criminal condition of a city in future is forecasted, an individual criminal map of the city is drawn, and the effects of promoting and regulating city public security and management are further achieved.

The invention provides a CPU virtualization method based on processor partitioning technology, which comprises the following steps: aiming at a multi-core or many-core platform, firstly, dividing a CPU core into a management core (H-Core) partition and a plurality of general core (G-Core) partitions; then, allocating management tasks and privileged domains in a VMM into the H-Core partition for operating; dividing general client domains operating on the VMM into different virtualization task subsets according to individual characteristics; and allocating the virtualization task subsets into the corresponding G-Core partitions for operating. Different scheduling policies and resource allocation policies can be realized aiming at different types of virtualization tasks in different CPU partitions. The CPU virtualization method of the invention improves the safety and the reliability of the virtualization system on the multi-core or many-core platform, reduces the complexity of CPU virtualization, simultaneously simplifies the complexity of overall resource allocation and scheduling, improves the capacity of the VMM for allocating and scheduling computing resources, and has the advantages of safety, reliability, high efficiency and high performance.

The invention discloses a navigation method based on iterative extended Kalman filter fusing inertia and monocular vision. The method is as follows: A monocular camera and an inertial measurement unitare mounted on the carrier. A message filter in ROS is used to realize that time stamp synchronization of the monocular camera and the inertial measurement unit. The position, velocity and rotation obtained by IMU are taken as the state variables of the system, and the position and attitude information obtained by vision sensor is used as the observation variables to establish the system equation. The position, velocity and rotation obtained by IMU are used as state variables of the system. The information obtained from the two sensors is fused by an iterative extended Kalman filter to realize the real-time state estimation and navigation of the carrier. The invention can maintain high precision in the long-time real-time positioning and navigation process, and has the advantages that thecomputational complexity between frames does not change.

The invention discloses a multi-template object tracking method based on CNN and CF. The present invention proposes a method of using a plurality of fixed scale values for normalizing the template before solving the convolution operation, and then reversing the most appropriate scale after obtaining the maximum response value; although the existing DSST algorithm is used to decompose the three-dimensional optimal scale search into the best position in two-dimensional space and the optimal scale mechanism is searched in one-dimensional space, the iteration is slow and the computational complexity is high; in view of the characteristics that the movement of the unmanned aerial vehicle platform is random, the speed is uncertain and so on, the method of the fixed scale value is used to not only meet the tracking algorithm needs, but also to meet the real-time operation; in the characteristic extraction stage, the two characteristics are extracted respectively, two different groups of filters are trained, according to the appearance and the background change of the current object, different weights are set for performing appearance representation of the object; and results obtained from the different characteristics are fused to obtain the tracking result.

This invention relates to one complete phase time displacement different frequency spectrum correction method, which measures the signal frequency rate, phase bit, range value parameters with high accuracy to make phase meter, frequency meter and spectrum analyzer, laser distant devices. The invention adopts technique key by use of whole phase FFT frequency spectrum analyze method for two existent lag relationship frequency spectrum to correct the analyze results by time displacement difference method and two time phase spectrum analyze results.

The invention relates to a rail transit fault diagnosis method and system based on a decision-making tree. The method includes the steps of firstly, determining various fault modes and various monitoring quantities of a rail transit device by analyzing a circuit and a mechanical structure model of the rail transit device; secondly, obtaining standard fault sample data according to various historical monitoring quantities of the rail transit device, then, analyzing the standard fault sample data through the decision-making tree generating algorithm, and conducting construction to obtain the decision-making tree of a fault; thirdly, collecting the various real-time monitoring quantities of the rail transit device, taking the decision-making tree as a classification model of the fault modes to conduct classification, and thereby determining the type of the fault. The system comprises a data collection device, a database unit, a data analysis unit and a knowledge base unit. The method and the device solve the technical problems that in the prior art, when the rail signal system fault is manually diagnosed, workloads are large, efficiency is low and the risks are high, and efficiency and accuracy of rail transit data analysis and fault diagnosis are improved.

An SOA system reliability evaluation method based on a complex network theory comprises four steps, belongs to the technical field of complex system reliability and aims at solving the problem that an SOA system is complex in structure and function and a traditional reliability analysis method is difficult to implement and even cannot be implemented and putting forward a methodology for effectively analyzing the reliability of the complex SOA system. The SOA system reliability evaluation method is characterized in that the method is innovatively integrated with the complex network theory, objects in the SOA system and the mutual effect of the objects are abstracted to be nodes and connecting lines in a complex network so as to establish a complex network failure model, a cascading failure model for the SOA system is put forward, and reliability analysis work is completed by utilizing a Monte Carlo simulation experiment on the basis so as to find key software and a weak structure influencing the system reliability. The SOA system reliability evaluation method is not limited by system scale, and increase of the system scale does not enable the calculation complex degree of the method to be remarkably improved. The SOA system reliability evaluation method is clear in physical significance and easily operated and implemented by engineers.

The invention relates to a wireless communication technical field, especially a LTE system CQI reporting implementation method. The invention provides a LTE system CQI reporting implementation method, capable of determining the coincidence relation between CQI sequence and I[TBS] and simulating and establishing the mapping relation between SINR and CQI. The invention provides a CQI reporting implementation method in LTE system multimode, capable of reporting the CQI sequence in multimode, wherein the mapping relation between SINR and CQI in one mode is used as the basis, based on the gradient, intercept relations between various transmission modes and the CQI sequences in other transmission modes are obtained by the fitting equation based on the mapping relation between the SINR and CQI sequence. The implementation method effectively solves the problem that many CQI combinations are formed by different cording rate and modulation mode and a large amount of emulations have a large amount of corresponding mapping relations, adverse to implement. The implementation method has simple implementation method and greatly saves the storage space.

This invention provides a correcting device and a correcting method for perspective transformation of document images. The correcting device comprises a horizontal vanishing point determining unit, for detecting a horizontal vanishing point of the perspective transformed document image; a vertical vanishing point determining unit, for detecting a vertical vanishing point of the perspective transformed document image; and a perspective transformation correcting and converting unit, for correcting the perspective transformed document image; wherein the horizontal vanishing point determining unit comprises a direct horizontal line segment detecting unit, an indirect horizontal line segment detecting unit and a horizontal vanishing point detecting unit, and wherein the horizontal vanishing point detecting unit detects a horizontal vanishing point in accordance with a direct horizontal line segment detected by the direct horizontal line segment detecting unit and an indirect horizontal line segment detected by the indirect horizontal line segment detecting unit.

The invention discloses a method for recognizing human face micro-expressions in a video sequence and relates to the treatment on a recording carrier for recognized patterns. A method for the extracting dynamic spatial-temporal textural characteristics of human face micro-expression sequences based on the HLACLF-TOP algorithm is provided. The method comprises the steps of amplifying the video of human face micro-expressions based on the Euler function, preprocessing the images of human face micro-expressions, extracting the dynamic spatial-temporal textural characteristics of human face micro-expression sequences based on the HLACLF-TOP algorithm, training and predicting by utilizing an ELM classifier. Based on the above method, the defect in the prior art that human face micro-expressions are hard to recognize due to the small variation amplitude of human face micro-expressions can be overcome.

The invention discloses an iterative least square method-based MIMO (multiple input multiple output) radar DOA (direction-of-arrival) estimation method, which is characterized in that receiving and transmitting array response matrixes on which dimension-reduced processing is performed are solved by using an iterative least square method. The iterative least square method-based MIMO radar DOA estimation method comprises the following steps: firstly, performing the dimension-reduced processing on echo data matrixes of multiple radar transmitted pulses and the receiving and transmitting array response matrixes; then, establishing cost functions under the least square condition, and solving the cost functions by utilizing a gradient descent-based iterative method; finally, estimating the direction of a target by utilizing known receiving and transmitting array manifolds. Compared with a traditional monostatic MIMO radar array DOA estimation method, the iterative least square method-based MIMO radar DOA estimation method disclosed by the invention directly obtains the DOA estimation of the target, and does not need to perform spectrum peak search. Noise is effectively suppressed by adopting the dimension-reduced processing, and the estimation accuracy under low signal to noise ratio is improved; the estimation, the inversion and the eigenvalue decomposition operation of high-dimensional data covariance matrixes are avoided; the defects that the calculated amount is high and the needed sample number is large when the traditional array DOA estimation method is applied to a monostatic MIMO radar are overcome.

A publicly-verifiable cloud data possession checking method is provided. The method includes the three stages of initialization, user challenge-response verification and TTP arbitration; the three stages comprise the following ten steps that: step 1, data segmentation [F->F'] is performed; step 2, verification tag generation [(SK, F)-> HVT] is performed; step 3, data and tag information upload [(F, HVT)->S] is performed; step 4, secret parameters are recorded to a TTP (trusted third party); step 5, the TTP verifies recorded parameters; step 6, [chal] is initiated by a user, and the chal and the verification information of the chal are handed over to the TTP so as to be record; step 7, a server makes a response; step 8, [(R, sk)->(' success', 'failure')] is verified; step 9, relevant information acquisition is verified; and step 10, the trusted third party performs verification publicly. With the publicly-verifiable cloud data possession checking method of the invention adopted, the user can verify the existence and integrity of data in a cloud storage server. The publicly-verifiable cloud data possessions checking method is advantageous in no limitation on the number of user authentication times as well as small storage capacity and low computational complexity of a client, and has great practical value and broad application prospect.

The invention belongs to the field of social network modeling and analysis, and particularly relates to a method for predicting the maximum information spreading range on the basis of a random model, and by means of the method, dynamic characteristics of a social network are explored. According to the method, a set of functions capable of describing the network information spreading dynamic characteristics are constructed, a dynamic information spreading model is built according to historical data of social network information spreading, a random model detector is used for predicting the possible maximum information spreading range through a verification and emulation technology, and the node set capable of maximizing the spreading range is found out, wherein information is spread through different node sets. Compared with a traditional spreading range maximization modeling method, the dynamic characteristics of the network can be modeled, so that the initial node set which is predicted out is higher in quality, and the success rate of a network marketing strategy is increased.

The invention discloses a video monitoring system and a moving target detecting and tracking method thereof. The method is applied to the video monitoring system on the condition that a camera is in a moving state. The method comprises the following steps: a moving target detection step, in which combination of a Harris corner and an HOG descriptor is employed as an image feature as well as processing including image feature extraction, image projection conversion, and image subtraction operation and the like is carried out to obtain a plurality of moving targets; a moving target model establishment step, in which moving target models are established for all the moving targets as well as a combination mode of a Harris corner, an extreme point and an HOG descriptor is employed to express features of the moving targets; and a target tracking step, in which target tracking is carried out according to the moving target models. According to the invention, corner feature matching is employed to reduce the calculated amount and precision of moving target detection is ensured; a corner and an extreme point are employed as target features, so that target identification has high robustness and tracking sustainability is strong; and a target motion estimation method is employed to reduce the calculated amount.

The invention relates to the technical field of gas-liquid two-phase flow measurement, in particular to a PCA mixed feature fusion based gas-liquid two-phase flow type identification method. The PCA mixed feature fusion based gas-liquid two-phase flow type identification method comprises: acquiring a flow type image by utilizing a high-speed camera; performing feature analysis on a preprocessed image; extracting three features including an invariant moment feature, a gray-level cooccurrence matrix feature and an LBP feature; performing fusion and dimension reduction on the three features, and performing classification identification by adopting a BP neutral network; and finally, applying a classification identification result to online automatic detection of two-phase flow. The three-feature fusion based method can better reflect image information. The mixed feature dimension number is relatively high, the calculation complexity is relatively high, and the consumed time is long, so that online detection is not facilitated. With the adoption of a PCA technology, the data dimensions can be effectively reduced, the calculation amount can be reduced, original information can be kept from being lost to a great extent, namely, little information is used for representing the original information as far as possible, and data are compressed.

A method of generating a value for a missing pixel “x” by determining a “least harmful” local edge direction between pixels, or sub-pixels, on substantially opposing sides of the missing pixel, and interpolating the difference to arrive at a value for pixel “x”. The method involves generating sub-pixel values for locations within neighboring pixels, the sub-pixels may comprise half-pixels, quarter-pixels, three-quarter pixels, and so forth, wherein any fractional pixel quantity may be created. Absolute difference values are calculated between neighboring pixels, or sub-pixel values, to determine a least harmful local edge direction along which a value is generated for pixel “x” by interpolation.

The present system discloses systems and methods for tracking planar shapes for augmented-reality (AR) applications. Systems for real-time recognition and camera six degrees of freedom pose-estimation from planar shapes are disclosed. Recognizable shapes can be augmented with 3D content. Recognizable shapes can be in form of a predefined library being updated online using a network. Shapes can be added to the library when the user points to a shape and asks the system to start recognizing it. The systems perform shape recognition by analyzing contour structures and generating projective invariant signatures. Image features are further extracted for pose estimation and tracking. Sample points are matched by evolving an active contour in real time.

The invention discloses a double-reconfigurable intelligent surface-assisted millimeter wave single base station positioning method, and belongs to the technical field of wireless positioning. The method comprises the steps: firstly, obtaining estimated angle information through angle estimation and collecting and summarizing by a BS side; selecting a proper RIS from two RISs according to the estimated angle information and path fading information for auxiliary positioning; and designing the phase shift of the RIS, then enabling a positioning reference signal sent by UE to reach BS through a direct path and a reflection path, solving a cross-correlation function of the two paths by the BS to obtain a path delay inequality, and further estimating the position of the UE, wherein the direct path represents the path from the UE to the BS, and the reflection path represents the path from the UE to the RIS plus the path from the RIS to the BS. According to the method, RIS auxiliary positioning is utilized, and positioning of the user equipment can be completed only through one base station; requirements on UE antenna configuration and software and hardware levels are extremely low, onlyextremely little calculation complexity is increased, and a positioning blind area of a community is effectively eliminated.

The invention relates to an inertial navigation platform and Beidou satellite-based high-precision and ultra-tightly coupled navigation method. According to the method, a stochastic linear time-invariant discrete system mechanical model is established according to a moving object state equation and a measurement equation; statistic analysis is performed on the first-order difference sequence and second-order difference sequence of redundancy measurement values of a system, so that a redundancy measurement-based adaptive Kalman filtering algorithm can be realized, and therefore, the measurement noises of the system can be estimated accurately, and noise variance R can be adjusted adaptively; according to a traditional ultra-tightly coupled structure, a neural network prediction module is introduced so as to be used for assisting a Beidou satellite carrier tracking loop and a code tracking loop under a lock loss state; a time delay filter is adopted for a Beidou satellite receiver, and therefore, the correlation between loop tracking errors and update time in the ultra-tightly coupled system can be significantly improved. The method of the invention belongs to the navigation control technical field and can be applied to high-precision navigation of carriers carrying strapdown inertial navigation platforms.

The invention discloses a seismic signal time-frequency decomposition method based on short-time fractional Fourier transform. A Gaussian window function is selected; high frequency resolution is obtained by adjusting the window width in a self-adapting way; through the characteristic of fractional kernel function angle rotation, the best energy accumulation of the seismic signal is obtained at the optimal rotation angle and the cross term is eliminated; the higher frequency resolution and more accurate frequency location are more conductive to recognizing specific geologic structure, so that the method solves the defects of the existing seismic signal time-frequency decomposition method. The method has the positive effects of overcoming the defects of traditional algorithm such as short-time Fourier and Wigner-Ville distribution and the like and having great significance on seismic signal spectral analysis.

The invention discloses a method of optimizing a departure interval of multiple bus lines collaboratively with a multi-objective model. The method includes the three steps of collecting basic relevant information, dynamically scoring, and solving for a multi-objective model. In the optimizing process, maximizing operation profits of bus companies is met, and minimizing the passenger waiting time and passenger travel cost is also considered, the interests of the two aspects of the bus companies and passengers are maximally ensured to be optimal, and comprehensive collaborative optimization is performed from the points of view of both the system and users. Considering the multiple aspects from multiple angles and combined with actual bus operation characteristics, the method of the invention is highly practical, can provide theoretical support for decision-makers of bus organization and management, maximally ensures the interests of both bus companies and passengers, improves the satisfaction of the passengers with the bus, greatly improve the operating efficiency of multi-line buses, and has important practical significance.

The invention discloses a multi-frequency range TETRA digital cluster detection apparatus and a detection method applying the apparatus. The apparatus comprises a multi-frequency range receiver radio frequency front end, a digital intermediate frequency processing plate, a reference source and a secondary power supply, and is characterized in that the multi-frequency range receiver radio frequency front end simultaneously receiving a multipath signal within any one frequency range; the digital intermediate frequency processing plate is in charge of processing of receiving data and control of a whole machine, and provides an external interface; the reference source provides a reference clock; and the secondary power supply supplies working power to the other aforementioned parts. By using the method and apparatus provided by the invention, the realization complexity and production cost of a TETRA digital cluster detection apparatus can be reduced, and the interference resistance is improved.

The invention discloses an H.264 compression bit stream oriented video watermark method. The method comprises the following steps of: generating an authentication code according to a predictive mode of a 4*4 brightness block in an I film; and embedding the authentication code in the film-grade bit stream by modulating variable-length code words of some motion sub-blocks of a B film and a P film, wherein the modulation is performed based on a mapping rule between the variable-length code words and the bits to be embedded, and the mapped variable-length code words is extremely similar to the original variable-length code words. Because in the method, the video bit stream is unnecessarily pre-processed, and comparison and replacement operations are performed by selecting the proper variable-length code words only from the H.264 / AVC compression bit stream in the watermark embedding process without a huge number of operations, so that the method has the advantages of low computing complexity, high safety and high practicability, and can better meet the requirements of the real-time video processing.

The invention provides an interferometer array integrated correction method. The method includes the steps of firstly, parameterizing a target signal initial incidence direction, a processing and installing comprehensive error and a feeder line passageway comprehensive error; secondly, obtaining a measuring equation set according to a known track rotation antenna array, and obtaining error parameters and incidence signal directions through parameter estimation; thirdly, modifying the error parameters into an interference angle measurement formula to obtain a precisely-corrected angle through the iteration technology. By means of the method, the incidence signal directions do not need to be accurately calibrated, the basic known quantities of the method are the rotation angle and the phase difference measurement value, the interferometer array processing and installing comprehensive error and the feeder line passageway comprehensive error can be obtained at the same time through parameter estimation, the problem that the direction error and the pitching error are coupled can be solved through the iteration technology when the angle measurement error correction is executed, and finally the precisely-corrected angle is obtained. The interferometer array integrated correction method is accurate in error model, simple in execution process, high in correction precision and capable of improving the correction efficiency and the angle measurement accuracy of an interferometer.

A method in a transmitting node in a wireless communication system for instructing a user terminal to perform uplink sounding is provided, said method comprising: generating an unlink grant in a downlink control information (DCI) for instructing the user terminal to transmit an uplink channel with only a reference signal; and transmitting the DCI with said uplink grant to the user terminal, and wherein said uplink grant is configured as a redundant state within the DCI. A method in a receiving node in a wireless communication system for performing uplink sounding is also provided.

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 a signal to leakage noise ratio (SLNR)-based two-stage precoding method in a large-scale MIMO FDD system. The operation complexity of precoding design of a first stage of each group of users is low, and the overall rate performance of the SLNR two-stage precoding method provided by the invention is superior to a JSDM precoding method proposed by Junyoung Nam et al. In addition, the method provided by the invention performs precoding design based on the SLNR of each group of users, does not cause channel state information loss, and does not influence performance of SLNR two-stage precoding even if angles of arrival of sending signals of two adjacent groups of users and a base station overlap.