49 results about "Levenberg–Marquardt algorithm" patented technology

Systems and methods for determining characteristic transition values such as elbow values in sigmoid or growth-type curves, such as the cycle threshold (Ct) value in PCR amplification curves. A double sigmoid function with parameters determined by a Levenberg-Marquardt (LM) regression process is used to find an approximation to a curve that fits a PCR dataset. Once the parameters have been determined, the curve can be normalized using one or more of the determined parameters. Normalization is advantageous for determining the Ct value if one chooses the arbitrary fluorescence level (AFL) approach to calculating Ct values for amplification curves. After normalization, the normalized curve is processed by applying a root-finding algorithm to determine the root of the function representing the normalized curve, which root corresponds to the Ct value. The Ct value is then returned and may be displayed or otherwise used for further processing.

A system and method for estimating a geolocation of a non-cooperative target using any reasonable target location estimate. Collectors may acquire actual signal measurements including a direction of arrival (DOA), a target range, a time difference of arrival (TDOA), a range rate, a range sum, and/or a frequency difference of arrival (FDOA). A processing device may receive the actual signal measurements and navigational data regarding the collectors. Then, the processing device may calculate an estimated target location as a solution to a nonlinear optimization problem where an objective function to be minimized is a weighted sum-of-squares of differences between the actual signal measurements and calculated values corresponding to signal measurements that theoretically should be produced for a particular target location. The algorithm used to solve this problem may be a globally convergent algorithm, such as a Levenberg-Marquardt algorithm.

Provided is a large-area complex-terrain-region unmanned plane sequence image rapid seamless splicing method which comprises the following steps: to begin with, with air strip arrangement features of unmanned plane image sequence being prior knowledge, carrying out inter-image multiple-overlap SIFT feature point extraction and matching; then, carrying out matching point gross error removing and purifying based on random sample consensus algorithm, and solving transformation parameters of each image in spliced regions in an adjustment manner through an Levenberg-Marquardt algorithm; next, carrying out overlapped region image optimized selection according to the relative position relationship between central projection image point displacement rules and the images, and determining splicing lines; and finally, carrying out image uniform-coloring and fusion at the edge-connection places, and outputting spliced images, thereby realizing mass unmanned plane image seamless splicing. The seamless splicing method helps to improve the extraction efficiency of the SIFT feature points, guarantee the geometric accuracy of the spliced images, and eliminate the tiny color difference at the two sides of the image splicing line, and thus the spliced images with natural color transition and good natural object and landform continuity are obtained.

The invention discloses an external parameter calibration method used when a camera and a two-dimensional laser range finder are used in a combined mode and relates to three-dimensional information image processing of objects. According to the external parameter calibration method used when the camera and the two-dimensional laser range finder are used in the combined mode, a foldable calibration plate is used for achieving external parameter calibration when the camera and the two-dimensional laser range finder are used in the combined mode, the foldable calibration plate is a long plane which is formed by splicing small rectangular black planes and small rectangular white planes alternately and can be unfolded and folded, the foldable calibration plate is unfolded when used, and the unfolding angle can be adjusted freely; calibration of internal parameter of the camera is achieved by means of a Matlab camera calibration tool box; a camera and two-dimensional laser range finder system is established; the foldable calibration plate is placed, and calibration is completed under the condition that the number of times of information acquisition of a system is smallest; image information and two-dimensional information are acquired and processed by the camera and the two-dimensional laser range finder respectively; processed camera information and processed two-dimensional laser range finder information are matched in a one-to-one mode for combined calibration; a calibration result is optimized by means of the Levenberg-Marquardt algorithm, and then calibration is completed.

The invention discloses a method for extracting the depth of a shallow buried pipe in a reclamation land, and the method comprises the steps: arranging a ground penetrating radar measuring line in a direction perpendicular to the distribution direction of the buried pipe, employing a high-frequency ground penetrating radar antenna for detection, and obtaining an original radar image of a research area; building a method based on the variance statistics, and extracting a target region of the buried pipe on a radar image; calculating the similarity level and correlation coefficient of adjacent echo signals, extracting feature points (shown in the description) of a reflection characteristic curve of a pipe target; carrying out the curve fitting of the feature points through employing a Levenberg-Marquardt algorithm, and obtaining the top point of a reflection characteristic curve; obtaining the electromagnetic wave propagation velocity based on the above through combining the diameter of the buried pipe and employing a least square algorithm, and finally calculating the depth of the buried pipe more accurately. The method employs the lossless detection technology based on the ground penetrating radar, and is a new method for the acceptance check of the land reclamation and consolidation projects of our country.

The invention discloses a two-dimensional plane iteration type camera calibration method. The method is characterized in that, on the basis of a two-dimensional visual measurement-based camera calibration method, the internal parameter of a camera is obtained. After that, a calibration plane is rotated by a certain angle around the origin OW of a world coordinate system, and then the internal parameter is solved again until the difference between parameters obtained every two adjacent times is smaller than a certain threshold value. Finally, an optimized objective function is built, and the calibration result is optimized through a levenberg-marquardt algorithm. Compared with a traditional two-dimensional visual measurement-based calibration method, the distortion of a lens in the shootingprocess is considered, and the calibration precision of the camera is improved.

The invention discloses a confocal axial response curve peak position extracting algorithm and belongs to the technical field of confocal scanning optical measurement. The method comprises the following steps of at first, normalizing data, and selecting effective data from measured data; taking a sinc4(a(x-b)) function as an objective function, and calculating the initial value of target parameter according to measured parameters; taking the sinc4(a(x-b)) function as the objective function, and using Levenberg-Marquardt algorithm to perform fitting to obtain the target parameter; according to the target parameter, calculating peak position. According to the confocal axial response curve peak position extracting algorithm, a confocal axial response curve peak position is obtained by taking sinc4 as the fitting objective function, so that data utilization rate and measurement uncertainty can be improved, meanwhile, iteration times is reduced, and the operation time of the extracting algorithm is reduced.

The invention discloses a laser tracker positioning method based on a laser tracker multi-position measuring system. The laser tracker positioning method comprises the following implementing processesthat a laser tracker multi-position measuring system is established; a laser tracker positioning is self-calibrated based on a Levenberg-Marquardt algorithm; and a parameter [mu]i is selected; lasertracer position coordinates are optimized; and the laser tracer position coordinates are optimized through the Levenberg-Marquardt algorithm and a singular value decomposition and transformation method of a covariance matrix. According to the laser tracker positioning method based on the laser tracker multi-position measuring system, the precision of the laser tracer position coordinates can be improved, multi-shaft machine tool coordinate errors are more accurately corrected, and thus the corrected results are more accurate.

The invention provides a Duhem-based piezoelectric actuator neural network parameter identification method. The method comprises the following steps: 1, a discrete parameter model is deduced by a Duhem model differential equation; 2, according to an interconnection relationship between the discrete parameter model and parameters, a neural network is built; 3, a static test principle is used to acquire an initial input and output data set for training of the neural network; 4, according to a Levenberg-Marquardt algorithm, the initial input and output data set and a preset training target, the neural network is trained, and according to a training result, a weight-adjustable value of the discrete parameter model is calculated; and 5, according to the discrete parameter model and the weight-adjustable value, values of the parameters are calculated.

The invention relates to an image rebuilding algorithm of DOT/XCT (diffuse optical tomography/X-ray computer tomography) dual-mode imaging based on a boundary element, and belongs to the technical field of molecular imaging. The method comprises the following steps of on the basis of providing an organization boundary by XCT , using a boundary element algorithm to solve the positive problem of DOT, namely solving the distribution of light flux at the boundary under the condition of known distribution of optical parameters of different organizations; and in the inverse problem, adopting a Levenberg-Marquardt algorithm to rebuild the absorption coefficients and scattering coefficients of different organizations, namely solving the absorption coefficients and scattering coefficients of the different organizations from the detected light flux data through the process of optimizing a non-linear minimum square model. Compared with the traditional rebuilding method based on finite elements, the boundary is utilized to rebuild in the DOT/XCT dual modes, and the rebuilding of the optical parameters of the organizations is more accurate and stable.

The invention discloses an elastic motion estimating method based on improved Levenberg-Marquardt optimization, and belongs to the field of video coding compression. Aiming at the defect that a Hessian matrix of a reference frame and an inverse matrix thereof need to be recalculated in the process of solving an elastic motion model with the traditional Gauss-Newton algorithm, the Hessian matrix of the reference frame is replaced by that of the current frame with reference to the thought of a Levenberg-Marquardt algorithm, and a hybrid Hessian matrix of the traditional Levenberg-Marquardt optimization algorithm is replaced by a Gauss-Newton Hessian matrix, so that the Hessian matrix and the inverse matrix thereof only need to be calculated once during each motion estimation; meanwhile, an early termination strategy is introduced, so that the purpose of reducing the elastic motion estimation calculation complexity is fulfilled.

The invention discloses a fisheye camera calibration system, method and device, electronic equipment and a storage medium. The system comprises a polyhedral target, a fisheye camera and electronic equipment; the polyhedral target comprises an inner surface and a plurality of marking layers arranged on the inner surface, and the inner surface is composed of a plurality of hexagonal planes and pentagonal planes; the fisheye camera is used for shooting the polyhedral target and collecting a target image, and the target image comprises the polyhedral target and images of a plurality of mark pointsarranged on the inner surface of the polyhedral target; the electronic equipment is used for obtaining initial values of k1, k2, k3, k4, k5, u0, v0, mu, mv, Tj and Rj; the initial values of k1, k2, k3, k4, k5, u0, v0, mu, mv, Tj, Rj are optimized by using the Levenberg-Marquardt algorithm to determine imaging model parameters of the fisheye camera.. Through the polyhedral target, a plurality of target images can be acquired without moving the target or a camera, and rapid and high-precision calibration of the fisheye camera can be realized only by acquiring one target image.

The invention provides a method for determinating the permeability of a fluid in a porous medium. The method comprises the following steps: establishing a control model for fluid flow in the porous medium by using a steady-state Stokes equation, and dividing the porous medium into a plurality of staggered grids; enabling a fluid to flow in the porous medium in a first direction, establishing a least squares objective function by selecting displacement pressure differences at different times and cumulative production as dynamic data on the basis of a radial-flow core displacement experiment, characterizing an oil-water relative permeability curve by using a cubic uniform spline model, and in combination with a radial-flow numerical simulator, continuously adjusting a control parameter vector of a phase permeability characterizing model by a Levenberg-Marquardt algorithm so as to minimize a quadratic sum of errors of observed values and predicted values of the dynamic data. According tothe scheme, the oil-water relative permeability curve can be accurately calculated on the basis of processing of radial-flow core displacement experimental data, and an effective tool is provided forstudying the percolation mechanism of oil, water, asphalt and a resin fluid in the porous medium.