33 results about "Inverse iteration" patented technology

The invention discloses a bilateral filtering de-noising method of point cloud data based on KDTree when a ground laser scanning technology is used to carry out measured object surface reconstruction. In a bilateral filtering algorithm, a scattered point cloud data point field is established through the KDTree so as to obtain a field point set of the data point. An inverse iteration method is used to calculate the field point so as to obtain a normal vector ni. A filtering function parameter and a filtering Gauss parameter are calculated so as to obtain a bilateral filtering power factor lambda. Finally, a new data point after the filtering can be obtained, wherein the new data point p'i=pi+ lambdani. The bilateral filtering method of the invention is used to filter the noise of the point cloud data. The method is simple and effective. An operation speed is fast. A characteristic can be maintained and simultaneously the noise can be removed. The method is suitable for processing the noise in a small scope.

The invention relates to a method for reconstructing a large-scale complex flyover 3D model by using airborne LiDAR data. The method includes the following steps: using inverse iteration mathematic morphological filtering and area information to extract flyover point cloud from airborne LiDAR data; in accordance with bridge floor connectivity, segmenting the flyover cloud point; adopting a central line vertical line scanning method to segment and extract a communicated bridge surface which has no bifurcation or intersection structures and has a width consistent width, acquiring a "constitutional unit"; an end place of the constitutional unit central line serving as a circular buffer area, detecting a shielding structure of the flyover through determination of point cloud height information within the buffer area; through steps of constitutional unit matching, 2D central line fitting and 3D curved surface fitting, acquiring a complete bridge surface 3D central line; and reconstructing a flyover 3D model in combination with bridge surface width information. Practice has proved that the method of the invention can effectively reconstruct the large-scale complex flyover 3D model, addresses shielding problem of the flyover point cloud, and the reconstructed 3D model has a higher correctness and completeness.

The invention relates to a tomography method of using the limb sounding data for inverting atmospheric ozone profiles. The method comprises the following steps: respectively calculating the intersections between the gaze vector and the atmospheric grid radial and vertical boundary and atmospheric layer horizontal boundary, merging two types of intersections, then calculating the distance between adjacent intersections to obtain intercept; applying the tomography method in a correlate equation about volume emissivity and radiance, using the square iterative reconstruction technology to obtain the inverse iteration model of the volume emissivity, calculating the volume emissivity; and finally using an oxozone photochemical model to connect the volume emissivity with the ozone number density, and selecting the Newton iteration method to invert the ozone profiles.

The invention provides a morphological analysis inverse iteration method for determining space structural lofting states of a cable-strut-beam system. The method includes: using a nonlinear finite element inverse iteration method with construction process considered, using an inactivating-activating unit method to positively simulate construction process influences based on assumption of the lofting similar state, using a morphological compensation method to inversely correct a lofting state geometrical configuration and pretension scheme, gradually astringing a positive tension analysis result of a lofting similar state to a preset design state through positive-inverse loop iteration, and finally obtaining a precise lofting state geometrical configuration and pretension control scheme.

A soft decision value output detector includes a plurality of maximum a posteriori (MAP) detectors. The MAP detectors are configured to simultaneously generate state metrics for portions of a sampled data sequence, and to generate soft decision values based on the generated state metrics. Each of the MAP detectors includes a first MAP unit that generates state metrics by a reverse iteration using first and second reverse Viterbi operators and a forward iteration using a first forward Viterbi operator through portions of the sampled data sequence, and a second MAP unit that generates state metrics by a reverse iteration using third and fourth reverse Viterbi operators and a forward iteration using a second forward Viterbi operator through portions of the sampled data sequence. The first forward Viterbi operator has a different convergence length than the first and second reverse Viterbi operators, and the second forward Viterbi operator has a different convergence length than the third and fourth reverse Viterbi operators. The first and second forward Viterbi operators may have twice the convergence length of first through fourth reverse Viterbi operators.

The invention provides a safety rate maximization synthesis method based on general inverse iteration in direction modulation, comprising the following steps of: before designing a useful signal beamforming vector and an artificial noise projection matrix, firstly initializing the two by using a leakage concept, then updating the artificial noise projection matrix by using a general power iterative (GPI), and synchronously updating the useful signal beam forming vector by the Rayleigh-Ritz method. In order to maximize the safety rate, an alternately iterative structure (AIS) is used in designing the useful signal beam forming vector and the artificial noise projection matrix, and the corresponding safety rate needs to be updated in time. Compared with the traditional direction modulationtechnology, the safety rate of the invention is greatly improved at a medium to high signal-to-noise ratio, a useful signal can be demodulated well in a desired direction and is difficult to recover in an undesired direction, thereby better improving the safety performance of the system.

The invention discloses a steel structure fire disaster temperature field inverse presumption method based on displacement forms. The method comprises the following steps that field investigation is conducted on a steel structure after a fire disaster, the structure is divided into different grids, the geometric center point of each grid is used as a displacement characteristic point, and displacement values of the displacement characteristic points are measured; a finite element calculation model is established; the established finite element calculating model is used for determining a temperature-displacement topological matrix between the temperature change of a structure rod piece in a single grid and displacement of the displacement characteristic points of the other grids; a temperature correction weight matrix is calculated according to the distance relationships between the displacement characteristic points; temperature field inverse iteration presumption is conducted. By means of the steel structure fire disaster temperature field inverse presumption method, temperature field distribution of the steel structure in the fire disaster can be accurately and quantitatively obtained and accurate input conditions is provided for finite element simulation of the steel structure after the fire disaster. The steel structure fire disaster temperature field inverse presumption method is high in result precision, has universality and has wide application prospects in the fields such as performance estimation, repair and reinforcement, disassembly scheme making of steel structures after fire disasters.

The embodiment of the invention provides equipment for identifying and controlling normal insertion and inverse insertion. The equipment comprises an interface male base, an interface female base, an inverse insertion recognition magnet, a Hall switch and a logic controller, wherein the Hall switch is connected with the logic controller; the logic controller is respectively connected with the interface male base and the interface female base; when the Hall switch does not detect magnetism, a high level signal is generated, so that the logic controller communicates a USB interface, connected with keys of a keyboard, with a channel of a CPU of a tablet PC and controls the USB Hub of the USB interface of a keyboard side to be communicated with a channel of the CPU of the tablet PC; and when the Hall switch detects the magnetism, a low level signal is generated, so that the logic controller disconnects the USB interface, connected with the keys of the keyboard, with the channel of the CPU of the tablet PC and controls the USB Hub of the USB interface of the keyboard side to be communicated with the channel of the CPU of the tablet PC. Therefore, identification and control on normal insertion and inverse insertion of a two-in-one computer are realized.

The invention provides an electric power system load flow calculation method based on hot start and a quasi-Newton method and relates to the technical field of electric power systems. The method comprises the following steps of firstly, establishing a linear power balance equation of a power system according to the structure and parameters of the power system, and obtaining an initial solution ofa bus node voltage; then determining a coefficient matrix M of quasi-Newtonian load flow calculation, and replacing inverse of a jacobian matrix in an iterative matrix equation of load flow calculation by using M to carry out power system load flow iterative calculation; introducing a relaxation factor into the coefficient matrix M, and searching an optimal value of the relaxation factor by utilizing a genetic algorithm; finally, calculating an initial coefficient matrix M0 according to the initial solution of the bus node voltage and the optimal value of the relaxation factor; and utilizing acoefficient matrix M to replace the inverse of the jacobian matrix in the iterative matrix equation of the Newton-Raphson method to carry out load flow calculation, carrying out load flow calculation, obtaining the voltage amplitude and a phase angle of a bus node of a power system, and obtaining the transmission power of each line.

The invention belongs to the technical field of structural topological optimization, and provides a nonlinear eigenvalue topological optimization method and system considering a frequency correlation material. The method comprises the steps of according to actual working conditions, dividing a structure into grids, adding boundary conditions, and through finite element analysis, obtaining a corresponding total stiffness matrix and a corresponding total mass matrix in the structure; constructing a non-linear eigenvalue equation based on the corresponding total stiffness matrix and the total mass matrix in the structure, and solving the non-linear eigenvalue equation by adopting a continuous asymptotic numerical method and an inverse iteration method to obtain a structural feature frequency and a corrected feature vector; and establishing a topological optimization model by taking the fundamental frequency maximization of the structure as a target and meeting the volume constraint as a constraint condition and combining the structural feature frequency and the corrected feature vector, inputting the material components containing the frequency correlation material structure into the model, and obtaining the material consumption meeting the requirement through topological optimization.

The invention discloses a joint detection algorithm applied to a massive MIMO uplink, which constitutes a joint detection algorithm with two external large iterations and two internal small iterations, wherein the external large iterations are respectively information interaction of a decoder and a detector and information interaction of interference estimation and the detector, and the internal small iterations are respectively the internal iteration of the detector LMMSE-ISDIC algorithm and the iteration of the decoder. The algorithm fully utilizes the iterative structure of the decoder to construct two large iterative structures similar to the Turbo turbine, which improves the detection accuracy of the large-scale MIMO uplink. Compared with the traditional uplink detection, the joint detection can sufficiently use the information interaction of each module to promote each other and jointly improve the final detection accuracy.

The invention discloses a form finding method of a cable net structure, which specifically comprises the following steps of: obtaining a group of coordinates and internal force of a cable net by utilizing a classical force density method in a non-load state, taking the configuration as an initial form, solving node coordinates and internal force of the structure under the load by continuously correcting the internal force of the structure under the load effect, namely afeasiable form, and completing form finding and force finding work. The coordinates and the internal force of the initial state are determined through the classical force density method, and the force density method is good in convergence and high in efficiency; the initial form is approximate to the feasible form, and the partial inverse iteration method only corrects the internal force of the cable net structure, so that the probability of algorithm divergence is reduced; the method can be combined with existing large finite element analysis software (such as ANSYS, SAP2000 and the like), and has good universality.

The invention discloses a real-time online instrument verification and diagnosis method through an adaptive support vector machine algorithm. The method comprises the following steps: S1, establishinga flow network model; S2, iterating field actual measurement data, and calculating and determining parameters in the model through an adaptive support vector machine algorithm to enable the model tobe available; S3, restarting the above steps regularly, and optimizing parameters; S4, verifying the sampled variables one by one by utilizing the model in a stable flow field state; s5, after the suspected failure point is eliminated, performing inverse iterative operation by using other data, and reversely deriving a theoretical calculation value of the suspected failure point; s6, eliminating process condition changes, performing comparative analysis on the actual instrument signal by using the theoretical calculation value, realizing verification and fault diagnosis, and determining a signal health level; and S7, recording a sampling signal and a calculation signal according to the measurement time, and giving an alarm and positioning a fault according to a deterministic fault diagnosis condition. Instrument faults can be found and reported early, results can be corrected intelligently, and work efficiency is improved.

The invention discloses a network coding-based scalable video stream encryption method. The method specifically comprises the following steps of first, pre-coding video stream data, so as to generate an image group sequence; then performing randomization on some data blocks of each layer in a plaintext message in each image group; next, performing linear randomization separately on the highest layer (the lowest transmission priority layer) of data, performing iterative transformation layer by layer according to a sequence from the second highest layer (the second lowest transmission priority layer) to a basic layer, and performing the same random linear combination on each data layer and data corresponding to an adjacent low priority layer simultaneously; and according to video quality subscription levels, decoding by each receiving terminal by using a layer-by-layer inverse iteration method. Through adoption of the method, quantitative security is realized in video stream security incremental encoding, further, in applications with different security demands, data confidential degree and video transmission coding and decoding flexibility are realized, the computing complexity is low, and the encryption efficiency is high.

The invention discloses a simple radar multi-target parameter extraction method. In the method, D is equal to three targets, when the number of targets is greater than 3, equations similar to equations (3) and (4) can be written in an imitating manner, but only the expression is relatively lengthy. The simple radar multi-target parameter extraction method specifically comprises the following steps: 1), estimating initial parameters of a signal direction, wherein when i ranges from 1 to D, D represents the sequence number of signals and is supposed to be equal to 3, if i is equal to 1, a formula shown in the description and another formula shown in the description are calculated so as to obtain an estimated target direction parameter initial value shown in the description, and i ranges from 1 to 3; 2), performing main iterative circulation, estimating a parameter shown in the description according to the initial parameters obtained in the step 1), thereby obtaining precise estimation on i, wherein i ranges from 1 to 3; 3), for the precise estimation on the value as shown in the description obtained in the step 2), calculating another two formulas shown in the description so as to obtain estimation on three target waveform parameters according to formula (4) and (8) shown in the specification, thereby providing parameter basis on target positioning and waveform identification, wherein i ranges from 1 to 3; when the number of the targets is greater than or equal to 3, writing a corresponding matrix shown in the description, Qi and expression of a projection matrix operator Pak,i according to existing expression such as P <A2-3> and matrix inversion iterative calculation relationship shown in the description. Therefore, the calculation complexity degree is substantially reduced, and the inversion errors can be avoided.

The invention discloses a spectrum inverse auction bidding method based on beam forming and power distribution. The spectrum inverse auction bidding method is characterized by comprising the following steps of: S1, establishing an inverse auction model; S2, carrying out beam forming and power distribution by a third-party base station; S3, establishing a bidding function of an owner of the third-party base station; and S4, establishing a target function of combining precoding with power distribution to carry out bidding design. According to the spectrum inverse auction bidding method disclosed by the invention, bidding reasonability of the owner of the third-party base station in the spectrum inverse auction model shared by the cellular network traffic can be well ensured, so that real value of all idle bands of the owner of the third-party base station is truthfully reflected; the spectrum inverse auction bidding method is easy to implement and convenient to expand; and bidding and a throughput of a third-party network are linked to establish the bidding function. Moreover, by utilizing beam forming and power distribution, the throughput of the third-party network in the inverse auction model is maximized, and the bidding function is optimized, so that the characteristic of truth of inverse auction is ensured.

The invention discloses a real-time online instrument verification and diagnosis method through an RBF particle swarm optimization algorithm. The method comprises the following steps: S1, establishinga flow network model; S2, iterating field actual measurement data, and calculating and determining parameters in the model through an RBF particle swarm optimization algorithm to enable the model tobe available; S3, restarting the above steps regularly, and optimizing parameters; S4, verifying the sampled variables one by one by utilizing the model in a stable flow field state; S5, after the suspected failure point is eliminated, performing inverse iterative operation by using other data, and reversely deriving a theoretical calculation value of the suspected failure point; S6, eliminating process condition changes, performing comparative analysis on the actual instrument signal by using the theoretical calculation value, realizing verification and fault diagnosis, and determining a signal health level; and S7, recording a sampling signal and a calculation signal according to the measurement time, and giving an alarm and positioning a fault according to a deterministic fault diagnosis condition. Instrument faults can be found and reported early, results can be corrected intelligently, and work efficiency is improved.