38 results about "Residual method" patented technology

The invention discloses a continuous operational reference system (CORS) base station cycle slip detection and recovering method, which comprises the following steps that: firstly, an ionized layer residual method is used for carrying out cycle slip detection, a satellite with the cycle slip and the corresponding observation value are determined, then, a single-epoch dual-frequency observation equation is built according to the cycle slip detection results, the single-epoch dual-frequency observation equation is divided into two types, the first type is cycle-slip-free observation equations, the second type is cycle slip observation equations, the cycle slip generated by a non-reference satellite is used as a gross error, the cycle slip generated by a reference satellite is used as a system error, the first type observation equations are used for carrying out parameter estimation, the cycle slip of the reference satellite is determined, the estimated parameters are introduced into thesecond type observation equations, correction numbers are calculated, the cycle slip values of the reference satellite are obtained, and finally, the cycle slip base station observation data is recovered according to the relationship between the base lines in a CORS triangular net. Because the error time strong correlation of the precise coordinate, the dual-frequency convection layer, the ionized layer and the like is directly utilized, the cycle slip detection and recovery can be precisely carried out.

The invention discloses a time division-synchronization code division multiple access (TD-SCDMA) system-based method for accurately positioning underground personnel. The method comprises the following steps of acquiring time of arrival (TOA) and an angle of arrival (AOA) of a signal at a base station; de-noising a TOA value by using an improved kalman filtering algorithm; calculating a time difference of arrival (TDOA) value according to the de-noised TOA value; estimating the position of a mobile station by using a TDOA / AOA mixed Chan algorithm and a TDOA / AOA mixed Taylor algorithm; performing first data fusion on a position estimated value by using a weighted residual method to obtain a new position estimated value; and performing second data fusion on the position estimated value by using Bayesian inference to obtain the final position estimated value. By the method for accurately positioning the underground personnel, the advantages of a TD-SCDMA system and the superiority of the data fusion are utilized, a TDOA / AOA mixed data fusion positioning algorithm is adopted, the positioning accuracy is high, and the problem that the personnel in an underground coal mine are hard to position is solved.

A calculation method for physical value for calculating physical values in a numerical analysis method for numerically analyzing a physical phenomenon, comprises a physical value calculation step of calculating physical values in an analysis domain divided into a plurality of divided domains, wherein in the physical value calculation step, the physical values are calculated by using: a discretized governing equation that uses values not requiring coordinates (Vertex) of vertices of the divided domains and connectivity information (Connectivity) of the vertices and that is derived on the basis of a weighted residual method; and a calculation data model in which volumes of the divided domains and characteristic values of boundary surface indicating characteristics of boundary surfaces of adjacent ones of the divided domains are provided as the values not requiring coordinates (Vertex) of vertices of the divided domains and connectivity information (Connectivity) of the vertices.

The present invention discloses an infrared weak small target detection method based on spectral residual and fuzzy clustering. The method comprises: inputting an original infrared image and performing normalization of the infrared image; performing filtering of the infrared image after normalization; obtaining the significance graph of the infrared image through a spectral residual method; performing clustering segmentation of the infrared image through adoption of local intuitionist fuzzy c mean clustering; adding a significance image and the image after clustering, and obtaining an image after fitting; subtracting the original infrared image from the fitting image to obtain a target significance graph; and searching a point with the maximum gray value in the graph, wherein the point is the position where the infrared weak small target is located. The infrared weak small target detection method based on the spectral residual and fuzzy clustering can perform effective combination of time domain information and frequency domain information of the infrared image, avoid the setting of a threshold through image fitting and improve the precision of image detection.

The invention brings forward a magnetotelluric meshless value simulation method for constructing a shape function on the basis of discrete nodes, for solving the problem of anisotropy widely existing in underground space media. It is assumed that one of electrical main shafts of an anisotropy medium is vertical to a bedding plane aspect and the other is parallel to a bedding plane direction, and thus a conductivity tensor model of an anisotropy medium model is constructed. For the purpose of solving an anisotropy magnetotelluric boundary value problem, an equivalent linear equation group corresponding to a meshless radical point interception method is derived, the shape function is constructed by compounding a multiquadric radial basis function (MQ-RBF) two times, and a large-scale sparse linear equation group is efficiently and accurately solved through QR preprocessing in a Krylov subspace and a quasi-minimal residual method (QMR). According to the invention, the constructed shape function is smooth and stable, complex distribution of physical property parameters of an electromagnetic method can be realized, and high-precision self-adaptive value simulation is realized.

The invention provides a three-dimensional frequency domain controllable source numerical simulation method. The method comprises the steps of S100: defining a calculation region in a resistivity anomaly body and an adjacent wrapping layer, and dividing the calculation region into multiple regular unit bodies; S200: calculating an initial electric field under an artificial source excitation condition, and by adopting a weighted residual method, establishing a finite element equation set of edge midpoints of the unit bodies in the calculation region; S300: defining an observation point as a boundary node by using a Green function, and enabling a secondary electric field of an internal node to express a secondary electric field of the boundary node; S400: substituting a Green function expression into a mixed equation set to obtain a first equation set only about the secondary electric field of the internal node; and S500: solving the first equation set to obtain secondary electric fieldvalues of nodes comprised in the unit bodies. According to the method, a vector finite element method and a volume integral equation method are applied; the calculation region is reduced; the calculation amount is reduced; the calculation precision is improved; formed equations are sparse in coefficient matrix and good in condition number; and a calculation result is accurate.

Disclosed is a phased-array antenna beam control system. A phased-array antenna is provided with phase shifters and a delayer; the two phase shifter channels in the sub-array level of the phased-arrayantenna correspond to one delayer. A phase shifter control code is calculated through a delay residual method, and then the phase shifting code is calculated by utilizing an intermediate frequency follow-up method. On the basis of the delay residual method, the intermediate frequency follow-up method is provided, and by adoption of the intermediate frequency follow-up method, the indexes of antenna broadband pointing error, gain, grating lobes and the like can be improved through algorithm optimization on the basis of not changing the hardware design of the delayer; and the algorithm not onlyhas high adaptability, but also can improve the performance of the antenna broadband directional diagram.

The invention relates to an unmanned aerial vehicle aerial video moving target detection method based on time-space-frequency significance. The method comprises the following steps of extracting the time significance of a video by utilizing a Lucas-Kanade optical flow method; extracting the spatial significance of the image by using color distribution; converting an image from a spatial domain toa frequency domain, extracting frequency domain significance of the image by utilizing a spectral residual method, carrying out linear weighted fusion on time, space and frequency domain significanceto obtain a significance confidence map, binarizing the significance confidence map by setting a threshold value, and extracting a moving target from an aerial video, so that the time domain significance, space domain significance and frequency domain significance are fused, the defects of the domains are overcome through the significance of the other two domains, the detection precision and the detection robustness are improved, the algorithm is simple, and the execution efficiency is high.

The invention discloses a residual correction method for NWP inversion tropospheric delay under multi-factor constraints. The method comprises steps: continuous one-year ZTD of all continuous runningreference stations in a working area and continuous one-year re-analysis data provided by the NWP in the area are firstly acquired; the ZTD of all continuous running reference stations in the area areinverted by using an integral method; the NWP inversion ZTD residual is fit based on a polynomial fitting method based on the minimum absolute residual method, and NWP prediction data and the initialcoordinates of an observation station at the current moment are acquired; by using the above residual model, the NWP_ZTD residual after correction at the current moment is calculated; the initial value of the NWP_ZTD at the current moment is inverted by using the NWP prediction data at the current moment; the initial value of the above NWP_ZTD and the NWP_ZTD residual after correction are added,and the accurate NWP_ZTD at the current moment is obtained. The method performs modeling for the first time based on the relationship between temperature, humidity, position and other factors and a tropospheric residual time sequence, the NWP inversion tropospheric delay residual is improved to improve the tropospheric delay estimation precision to a sub-centimeter level.

The invention discloses a multi-scale thermal inertia model inversion-based method for measuring the moisture content of surface soil. The method for measuring the moisture content of the surface soilcomprises the following steps: performing discrete wavelet transform analysis on an acquired ASTER thermal infrared image to acquire a high-definition ASTER thermal infrared image; acquiring and calculating a surface component temperature according to the high-definition ASTER thermal infrared image; calculating a surface albedo through a weight function for converting a narrow band albedo into awide band albedo; estimating a surface sensible heat flux according to the high-definition ATER thermal infrared image; calculating a surface latent heat flux by an energy residual method according to the surface sensible heat flux; calculating a thermal inertia of the soil according to the surface component temperature, the surface sensible heat flux, the surface latent heat flux and the surfacealbedo; and building a surface soil moisture content inversion model according to the thermal inertia of the soil. By implementation of the method of the embodiment, the measurement precision of themoisture content of the soil within a detected region can be effectively improved.

The invention belongs to the technical field of unmanned aerial vehicle (UAV) detection, in particular to an infrared small target detection method for complex scenes. The invention suppresses a largenumber of backgrounds by using an improved morphological filter and separates the backgrounds. A saliency detection algorithm combined with fractional derivative is proposed, an eight-direction fractional-order differential operator is used to enhance the gray level of the object, the background noise can be suppressed slightly, and then the spectral residual is used for significant target detection and target extraction, which is better than the single direct use of spectral residual method for detection, and the obtained target is more significant, so that the purpose of high detection rateand low false alarm rate detection can be achieved for infrared weak and small target in the field of view in a plurality of scenes.

The invention belongs to the technical field of image processing, in particular to a vehicle logo positioning method. Most of the existing vehicle logo positioning methods use traditional methods, thepositioning rate and robustness are poor. The invention provides a vehicle logo positioning method, which comprises the following steps: step 1): acquiring a vehicle front face image; 2) extracting primary features of that image; 3) calculating and fusing that final saliency map by adopting a multi-scale spectrum residual method, dividing the saliency map into a plurality of sub-salient regions,and forming a plurality of attention focuses; Step 4), calculating the complexity of each area; step 5), adopting the improved ant colony algorithm to optimize the focus transfer path; step 6), determining the vehicle logo area. The vehicle logo positioning algorithm of the application has better positioning rate and robustness.

The invention provides a fan sensor-based drift correcting method. The fan sensor-based drift correcting method comprises, firstly, collecting generator operation data within the time period of T1 through a fan sensor, and eliminating abnormal data; secondly, based on a generator simulation model, creating a multi-variable power matrix to structure a numerical reference system; thirdly, taking wind deviation within T1 as fixed wind deviation to acquire an relation of incoming flow direction and detected wind direction to determine that measured power is in linear correlation with difference power acquired through the multi-variable power matrix; fourthly, through the optimal linear correlation method or the least residual method, solving out an optimal solution; lastly, inputting the acquired optimal solution into a fan control to perform drift compensation and accordingly to achieve generation drift correction. On the basis of not adding devices, the fan sensor-based drift correctingmethod solves the problem of deviations existing in fan wind direction measurement, achieves zero-cost drift correction and is high in reliability and free from maintenance. The fan sensor-based driftcorrecting method can be applied in scales to existing generators to effectively improve the accuracy of drifted wind alignment of wind generators and further to improve the generating capacity of the wind generators.

The invention discloses a target sensing method based on compressed sensing classification. The method comprises the following steps that 1) significance test is carried out on a target image in a spectral residual method to obtain a corresponding pixel significance figure; 2) points of significance in the pixel significance figure are ordered according to the significance; 3) the most N significant points of significance are selected as focusing points, and a minimal rectangle which includes the focusing points serves as a focusing area; 4) pixels within the focusing area are sampled randomly, and pixels, of the same amount, beyond the focusing area are sampling randomly; and 5) a dichotomy pixel classification model is obtained by utilizing the compressed sensing classifier strategy, all the pixels of the target image are classified by the model, and an pixel area of a positive class serves as a first focusing target area. According to the human visual focusing process, human visual sense is simulated by focusing points ordering and the pixel classification model, so that a target scene is rapidly focused, and a machine can visually sense the target scene.

A video device may generate an enhanced inter-layer reference (E-ILR) picture io assist in predicting an enhancement layer picture of a. scalable bitstream. An E-ILR picture may include one or more E-ILR blocks. An E-ILR block may be generated using a differential method, a residual method, a bi-prediction method, and / or a uni-prediction method. The video device may determine a first time instance. The video device may subtract a block of a first base layer picture characterized by the first time instance from a block of an enhancement layer picture characterized by the first time instance to generate a differential block characterized by the first time instance. The video device may perform motion compensation on the differential block and add the motion compensated differential picture to a block of the second base layer picture characterized by the second time instance to generate an E-ILR. block.

The invention discloses a local error driving isogeometric analysis computational domain self-adaptive optimization method. An isogeometric analysis method requires the optimization on all internal control top points, so the isogeometric analysis method is only applicable to a condition that a computational domain is in a simple shape. According to the method, firstly, a residual method is utilized for obtaining a local error indicator on a computational domain sub chip; then, a control top point set to be optimized is determined according to a local marking strategy; the optimum distribution of the marked internal control top points is obtained through marking the error indicator on a curve chip; a self-adaptive (h-r) type refinement algorithm is provided on the basis of a self-adaptive r type refinement algorithm; and the optimum parameterization of the computational domain is obtained. The method has the advantages that the simulation emulation efficiency and the isogeometric analysis solving precision are improved; the r type refinement algorithm can be applied to CAD models with complicated geometrical shapes; and the application range of the isogeometric analysis method is widened.

The invention discloses a numerical calculating method for accelerated solution of a burn-up equation by the Krylov subspace, based on a rationally developed matrix index method, the burn-up solutionspeed is improved on the premise of ensuring a certain precision requirement by coupling a new Krylov subspace method, namely, a generalized minimum residual method. The main purpose is to project ann-dimensional burn-up matrix and an initial nuclide concentration onto an m-dimensional subspace, and then find the optimal solution in this subspace. Since the dimension m of the subspace is much smaller than the dimension n of the burn-up matrix itself, the amount of calculation is greatly reduced during solution, and the calculating speed is greatly improved.

Provided is a method for acquiring a residual static correction value. The method comprises the steps that common midpoint way set data after dynamic correction are read in, and statistics is carried out on the number of shot points in the data and the number of demodulator probes in the data; according to the number of the shot points, the number of the demodulator probes and a preset residual static correction value search range, an initial solution set is generated; a Poisson disk sampling algorithm is utilized for obtaining a sampling solution set according to the initial solution set, and the sampling solution set is mapped to a genetic space through real number coding to form an initial population; the genetic manipulation is carried out on the initial population, and an individual meeting the preset conditions is acquired as the residual static correction value. According to the method, the evolution speed and effect of the solving process of the residual static correction value can be improved.

The invention discloses a time division-synchronization code division multiple access (TD-SCDMA) system-based method for accurately positioning underground personnel. The method comprises the following steps of acquiring time of arrival (TOA) and an angle of arrival (AOA) of a signal at a base station; de-noising a TOA value by using an improved kalman filtering algorithm; calculating a time difference of arrival (TDOA) value according to the de-noised TOA value; estimating the position of a mobile station by using a TDOA / AOA mixed Chan algorithm and a TDOA / AOA mixed Taylor algorithm; performing first data fusion on a position estimated value by using a weighted residual method to obtain a new position estimated value; and performing second data fusion on the position estimated value by using Bayesian inference to obtain the final position estimated value. By the method for accurately positioning the underground personnel, the advantages of a TD-SCDMA system and the superiority of the data fusion are utilized, a TDOA / AOA mixed data fusion positioning algorithm is adopted, the positioning accuracy is high, and the problem that the personnel in an underground coal mine are hard to position is solved.

The invention provides a fan sensor-based drift correcting method. The fan sensor-based drift correcting method comprises, firstly, collecting generator operation data within the time period of T1 through a fan sensor, and eliminating abnormal data; secondly, based on a generator simulation model, creating a multi-variable power matrix to structure a numerical reference system; thirdly, taking wind deviation within T1 as fixed wind deviation to acquire an relation of incoming flow direction and detected wind direction to determine that measured power is in linear correlation with difference power acquired through the multi-variable power matrix; fourthly, through the optimal linear correlation method or the least residual method, solving out an optimal solution; lastly, inputting the acquired optimal solution into a fan control to perform drift compensation and accordingly to achieve generation drift correction. On the basis of not adding devices, the fan sensor-based drift correctingmethod solves the problem of deviations existing in fan wind direction measurement, achieves zero-cost drift correction and is high in reliability and free from maintenance. The fan sensor-based driftcorrecting method can be applied in scales to existing generators to effectively improve the accuracy of drifted wind alignment of wind generators and further to improve the generating capacity of the wind generators.

The invention provides a display panel, a display device and an anti-static residual method of the display panel. The display panel comprises a first substrate and a second substrate which are oppositely arranged, a liquid crystal layer positioned between the first substrate and the second substrate, at least one common electrode block, and high-resistance film blocks positioned on one side, facing the liquid crystal layer, of the first substrate. The high-resistance film blocks are arranged in an array mode, and the positions of the high-resistance film blocks correspond to the position of one or more public electrode blocks; the high-resistance film blocks are used for electrostatic residue responding to the corresponding common electrode block for heating the liquid crystal layer. The display panel provided by the invention is provided with the matrix-shaped common electrode blocks and the high-resistance film blocks near the liquid crystal layer, and perform heating for the electrostatic residue through the high-resistance film blocks to speed up the dissipation rate of the electrostatic residue on the display panel so as to achieve the purpose of accurately and quickly eliminating the electrostatic residue on the display panel.

The invention discloses a method for evaluating the influence of the peasant-workers on the total factor productivity of the building industry based on a solow residual method, which is characterizedby comprising the following steps of 1) clarifying an analysis object, forming a plurality of evaluation units; 2) establishing a measurement system, determining an input variable, an output variableand a specific measurement index; 3) carrying out scene construction, setting two production scenes A and B which do not comprise peasant workers; 4) collecting the data according to the established measurement system; 5) measuring the change of the total factor productivity in the production scene A; obtaining a total element productivity growth sequence {SRA} of the production scene A; 6) measuring the change of the total element productivity in the production scenario B to obtain a total element productivity increase sequence {SRB} of the production scenario B; 7) calculating the influenceof the peasant-workers on the total factor productivity. The method has the advantages of being easy to measure, being comprehensive in factor consideration, accurate in calculation, verifiable in assessment result and the like, and being able to improve the evaluation accuracy of the total factor productivity of the building industry.

The invention relates to a residual oil hydrotreating method performed in a residual oil hydrotreating device comprising a hydrodesulfurization reaction zone, a hydrodemetallation reaction zone, a first high-pressure separator, a second high-pressure separator and a fractionating system. The method comprises the following steps: a residual oil raw material, an effluent generated in the hydrodesulfurization reaction zone and a first hydrogen gas material flow are injected into the hydrodemetallation reaction zone and are subjected to a reaction; an effluent generated in the hydrodemetallation reaction zone is injected into the first high-pressure separator and is separated; a part of a separated liquid-phase effluent and a second hydrogen gas material flow are injected into the hydrodesulfurization reaction zone and are subjected to a reaction; and the separated gas-phase effluent is injected to the second high-pressure separator and is separated, and the separated liquid-phase effluent and the other part of the liquid-phase effluent separated by the first high-pressure separator are injected to the fractionating system and are fractionated. The residual oil hydrotreating method provided by the invention can significantly improve the impurity removal rate, product distribution and operation stability.

The invention discloses a load identification method for bridge moving vehicles based on the generalized minimum residual method. (1) Arranging photoelectric sensors, strain gauges and accelerometers at the preset measuring points on the bridge deck; (2) Building bridges Simplify the physical mechanics model, (3), solve in the time domain by convolution integration, obtain the system equation of the form such as, then be the known system matrix, be the known bridge deck response, be the moving vehicle load that seeks; (4) Give an initial value to the mobile vehicle to obtain the initial residual; (5) Use the generalized minimum residual method to obtain the mobile load. Compared with common mobile load identification methods, the identification accuracy of the invention is greatly improved, and is especially suitable for high-precision mobile load identification.

The invention provides a feature extraction method for signals of an electronic tongue based on manifold learning. The method comprises the following steps: detecting tea samples with the electronic tongue so as to obtain sensor-responsive sequence signals; analyzing and rejecting abnormal samples by using a principal component residual method and a Mahalanobis distance method; optimizing the parameters of a manifold learning algorithm and selecting the parameters of the manifold learning algorithm on the basis of the correct recognition rata of the quality grade of Longjing tea; carrying out non-linear feature extraction on sensor-responsive signals by using the manifold learning algorithm so as to obtain characteristics characterizing the taste information of the tea samples; and inputting the taste characteristics of the tea samples into a classifier and determining the quality grade of the Longjing tea. The feature extraction method can reject the abnormal values of the tea samples; and the parameter-optimized manifold learning algorithm can better characterize the non-linear characteristics of tea samples of different grades and improve signal difference of samples having undergone nonlinear mapping in high-dimensional feature space.

The invention discloses a continuous operational reference system (CORS) base station cycle slip detection and recovering method, which comprises the following steps that: firstly, an ionized layer residual method is used for carrying out cycle slip detection, a satellite with the cycle slip and the corresponding observation value are determined, then, a single-epoch dual-frequency observation equation is built according to the cycle slip detection results, the single-epoch dual-frequency observation equation is divided into two types, the first type is cycle-slip-free observation equations, the second type is cycle slip observation equations, the cycle slip generated by a non-reference satellite is used as a gross error, the cycle slip generated by a reference satellite is used as a system error, the first type observation equations are used for carrying out parameter estimation, the cycle slip of the reference satellite is determined, the estimated parameters are introduced into thesecond type observation equations, correction numbers are calculated, the cycle slip values of the reference satellite are obtained, and finally, the cycle slip base station observation data is recovered according to the relationship between the base lines in a CORS triangular net. Because the error time strong correlation of the precise coordinate, the dual-frequency convection layer, the ionized layer and the like is directly utilized, the cycle slip detection and recovery can be precisely carried out.

The invention discloses a method for manufacturing a patterned sapphire substrate with a residual-layer-free nano-imprinting technology. The method comprises the steps that (1) adhesion preventing treatment is carried out on the surface of a composite nano-imprinting template; (2) a proper gumming thickness is selected to carry out imprinting by calculating the feature and the duty ratio of the patterns of the composite nano-imprinting template; (3) the gumming thickness is controlled by controlling the gum evening speed, gum evening time and concentration of nano-imprinting gum and other influence factors, and the sapphire substrate is coated with the imprinting gum; (4) pressurization is gradually carried out through quartz plates to carry out imprinting, proper imprinting pressure is selected, exposure is carried out for 15 minutes under ultraviolet light, and nano-imprinting gum is solidified; (5) the quartz plates and the composite nano-imprinting template are removed, residual-layer-free nano-imprinting patterns are obtained, the patterns are used as masks, and the sapphire substrate is etched to obtain the patterned sapphire substrate. The patterned substrate copied through the method is high in pattern resolution ratio, good in repeatability and more beneficial for the industrialization of the patterned sapphire substrate.

The invention discloses a local error driving isogeometric analysis computational domain self-adaptive optimization method. An isogeometric analysis method requires the optimization on all internal control top points, so the isogeometric analysis method is only applicable to a condition that a computational domain is in a simple shape. According to the method, firstly, a residual method is utilized for obtaining a local error indicator on a computational domain sub chip; then, a control top point set to be optimized is determined according to a local marking strategy; the optimum distribution of the marked internal control top points is obtained through marking the error indicator on a curve chip; a self-adaptive (h-r) type refinement algorithm is provided on the basis of a self-adaptive r type refinement algorithm; and the optimum parameterization of the computational domain is obtained. The method has the advantages that the simulation emulation efficiency and the isogeometric analysis solving precision are improved; the r type refinement algorithm can be applied to CAD models with complicated geometrical shapes; and the application range of the isogeometric analysis method is widened.