31 results about "Quadratic error" patented technology

The link adaptation process for selecting a physical layer mode used on a radio link for transmitting symbols of a message between two stations of a wireless communication system among a set of potential physical layer modes comprises the steps of: —evaluating the current radio link conditions; and switching from a current physical layer mode to another physical layer mode by applying a criteria depending on the evaluated current radio link conditions. The evaluation step of the current radio link conditions comprises the calculation of a received modulation accuracy (RMA) for at least a part of the message, the received modulation accuracy (RMA) being de\-fined as the inverse of the expectation of a quadratic error for a predetermined number of symbols between demodulated received symbol values and ideal symbol values and in that the criteria is at least partially dependent on the calculated received modulation accuracy (RMA).

The invention discloses a three-dimensional grid model simplification method and system method and system based on optimized feature preservation. The three-dimensional grid model simplification method includes the steps: firstly, calculating the Gaussian curvature of each edge in a three-dimensional grid, combing the Gaussian curvature and the secondary error measure of the edge to calculate thefolding cost of the edge, and constructing edge folding operation based on feature preservation; combining an edge splitting operation sequence and an edge folding operation sequence based on featurepreservation to generate a mixed sequence, and using a mixing mechanism for simplifying a three-dimensional grid model; replacing a global search stage in whale optimization by crossover and mutationoperation of differential evolution, and constructing a whale differential evolution optimization algorithm; and finally, searching an optimal edge splitting operation and edge folding operation sequence combination mode by utilizing an optimization algorithm, so that the approximate error between the simplified three-dimensional model and the original model is minimum. According to the three-dimensional grid model simplification method, through grid simplification, the optimal three-dimensional grid simplification effect with the minimum approximate error can be obtained, meanwhile, geometrical characteristics can be well kept, and the quality of triangles in the model is improved.

The invention relates to the field of computer graphics and discloses a mean quadratic error metrics edge contraction simplifying method. The mean quadratic error metrics edge contraction simplifying method comprises a mean quadratic error metrics method and an edge contraction simplifying method based on the mean quadratic error metrics method. The mean quadratic error metrics method comprises the steps of collecting all vertices in a model and updating the vector quantities of all triangular surfaces. The edge contraction simplifying method comprises the steps of selecting all proper vertex pairs, calculating the contraction target vertex and error value of each vertex pair, ranking the vertex pairs in an ascending order according to the error values, placing the ranked vertex pairs in a vertex pair list, and finally traversing the list from the start, removing the vertex pairs, contracting the vertices and updating the error values of corresponding vertex pairs. According to the edge contraction simplifying method adopting mean quadratic error metrics, the mean quadratic error matrix of the vertices is calculated by means of the parallel computing power of a GPU, and time required by the initialization phase during quadratic error metrics is shortened greatly.

A prediction-correction model-based mesh simplification method is disclosed. The mesh simplification method of the calibration model comprises the following steps: reading all vertices and surfaces inthe three-dimensional mesh, and calculating the basic quadratic matrix and the quadratic error matrix; calculating the initial folding errors of all edges and the positions of the corresponding new vertices, and inserting the initial folding errors into the priority queue; selecting the edge with the least folding error from the priority queue, performing a folding operation, and updating the related vertices and faces; recalculating the basic quadratic matrix of the adjacent surfaces and the quadratic error matrix of the new vertices according to the positions of the new vertices; recalculating the folding error of the edge adjacent to the folding point and the position of the corresponding new vertex, and updating the priority queue; stopping operation until the simplified conditions set are satisfied. The invention can effectively control the accumulated error in the process of edge folding, improve the quality of the simplified model and improve the overall simplified effect whilerapidly and efficiently simplifying the mesh.

Detection method and device for a receiver in a digital communication system designed to process a frame comprising a periodic sub-set of length n, said method comprising the following steps: —determining a first vector u having a length n;—determining a second shifted vector v;—calculating a correlation function between said first and second vectors; —calculating a quadratic error function between said first and second vectors;—calculating a first cost function that is a linear combination of both preceding functions and, according to the sign of the result,—calculating a second cost function of frame beginning estimate; and—starting the communication system receiver.

The invention relates to a digital twinning-oriented scene lightweight method, which comprises the steps of 1, inputting model data, calculating a quadratic error metric matrix considering constraints, calculating an optimal folding point and a corresponding folding cost, gradually taking out an edge with the minimum folding cost for folding, and generating a simplified three-dimensional network model; 2, calculating the surface discrete curvature of the vertex of the three-dimensional network model, finding out a point of which the curvature value is less than that of all adjacent points in a multi-direction gradient descent mode to serve as a local minimum value point, on the basis of the vertex with the minimum local curvature, carrying out region marking, flat region marking and region segmentation marking on neighborhood vertexes, and combining over-segmented regions by using region clustering; and 3, calculating Euclidean geometric distances among the planes after segmentation and combination, and generating a final lightweight model. According to the method, the full-working-condition self-adaptive three-dimensional grid model can be lightened for digital twinning operation scene optimization.

The invention discloses a grid simplification method considering the area and normal vector for the non-smooth surface. The estimated error of each edge folding and the position of the new vertex, the normal vector constraint is included in the cost of the new vertex after folding, the minimum folding cost and the corresponding position of the new vertex and the original vertex are stored in the vertex attribute, and the folding error Insert into the priority queue; take out the edge with the least folding cost from the queue, fold it, and update the relevant vertices and faces; until the set simplification conditions are satisfied. The present invention can keep the detail features of the original model as much as possible while quickly simplifying the grid. Especially for some non-fluid and non-smooth surfaces, compared with the traditional method, this method can better preserve the details and achieve a more prominent simplification effect, thereby improving the overall simplification effect.

The embodiment of the invention discloses a model simplification method and related equipment thereof. The method comprises the steps: firstly determining a quadratic error matrix and curvature representation data of at least one vertex in a to-be-simplified model after the to-be-simplified model is obtained; respectively determining a quadratic error matrix and curvature representation data of at least one vertex pair according to the quadratic error matrixes and curvature representation data of the vertexes; then, according to the quadratic error matrixes of the vertex pairs and curvature representation data, the merging cost of the vertex pairs is determined; and finally, according to the combination cost of the vertex pairs, performing vertex combination processing on the to-be-simplified model, so that the number of vertexes in the to-be-simplified model obtained through vertex combination processing is less than the number of vertexes in the original to-be-simplified model. Therefore, less resources are consumed when subsequent model processing is carried out on the to-be-simplified model obtained through vertex merging processing, and the processing effect on the high-dimensional data model can be improved.

The invention relates to the field of computer graphics, and discloses a mean quadratic error measuring method. The mean quadratic error measuring method comprises the steps that all vertexes in a model are collected, and the vectors of all triangular faces are updated; according to the specific steps, a vertex error is defined as the sum of the squares of the distances between the vertexes and all the triangular faces adjacent to the vertexes according to a QEM algorithm; calculation of the vertex error is transferred o a GPU end; a pixel value is defined, and a row vector is converted into the pixel value and placed in Color Buffer; the pixel value is acquired from the Color Buffer and is reverted to a mean quadratic error matrix; the computational formula of the second order error can be obtained according to the computational formula of the vertex error. The mean quadratic error measuring method is provided, the QEM algorithm is adopted, calculation of the vertex error is transferred to the GPU end, the pixel value is acquired from the Color Buffer and reverted to the mean quadratic error matrix, and time needed in the initialization stage of second order error measurement is greatly shortened.

The invention discloses a three-dimensional model classification retrieval method based on kernel sparse representation. The method comprises the following steps: 1, carrying out vertex simplificationprocessing on a three-dimensional model represented in a point cloud form by using an edge shrinkage algorithm based on a secondary error as a measurement cost; 2, calculating the direction of the three-dimensional model after vertex simplification, ensuring that the same kind of models can be aligned in the direction, and obtaining three characteristic direction vectors of the three-dimensionalmodel through calculation; 3, rendering the three-dimensional model based on the three characteristic direction vectors to obtain a plurality of different rendered images in corresponding different directions; 4,for the characteristics of the three-dimensional model in different data sets, comprehensively considering data characteristics and descriptor characteristics, and selecting a characteristic descriptor to extract the characteristics of the rendered image; and 5, matching the extracted feature vectors by using an improved kernel sparse representation classifier so as to realize the classification retrieval work of the three-dimensional model. The method has certain robustness, and relatively high-efficiency and reliable superior performance is obtained.