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38 results about "Discretization error" patented technology

In numerical analysis, computational physics, and simulation, discretization error is the error resulting from the fact that a function of a continuous variable is represented in the computer by a finite number of evaluations, for example, on a lattice. Discretization error can usually be reduced by using a more finely spaced lattice, with an increased computational cost.

C-arm tomography imaging method using semi-accurate filtered back-projection

The invention discloses a tomography imaging method suitable for C-arm imaging equipment. The tomography imaging method is characterized by having shift invariant features, wherein the semi-accurate reconstruction is performed on cone-beam projection data obtained by scanning a circular arc track. The circular arc track is a short scanning track, namely a scanning track of pi and a fan angle, and is also an ultra-short scanning track, namely a track smaller than the short scanning track. The method comprises the following steps: weighing of partial derivatives of projection data; one-dimensional Hilbert transform in a horizontal or non-horizontal direction; and back projection of the circular arc track. Compared with FDK type-approximate reconstruction algorithms, the C-arm tomography imaging method using semi-accurate filtered back-projection has the advantages of small reconstruction accuracy error, small discretization error and the like.
Owner:UNIV OF ELECTRONIC SCI & TECH OF CHINA

Discretized differentiable neural network search method based on entropy loss function

The invention discloses a discretized differentiable neural network search method based on an entropy loss function. According to the method, a new loss term is designed into a constraint loss term suitable for different target network structure configurations based on an entropy function according to the characteristics of system entropy minimization driving system element (weight) sparsity and discretization so as to reduce discretization errors. According to the discretized differentiable neural network search method based on the entropy loss function, a discretized friendly target networkstructure is obtained through one-time search, and discretization precision loss existing in an existing search algorithm is greatly reduced; parameters of an entropy function-based structural constraint loss function may be modified to be adapted to search for arbitrarily configured network structures.
Owner:UNIVERSITY OF CHINESE ACADEMY OF SCIENCES

Tunnel resistivity modeling method and system based on hybrid grid

The invention provides a tunnel resistivity modeling method and system based on a hybrid grid. The method comprises the following steps: determining the physical size, the actual shape, the power supply and acquisition electrode position and the possible unfavorable geological area of a tunnel to be modeled; establishing a finite element geometric model according to the actual shape and size of the tunnel; carrying out mesh generation on the finite element geometric model, carrying out non-structural tetrahedral mesh local encryption subdivision on power supply and acquisition electrode positions and possible unfavorable geological areas, and carrying out mesh generation on other uniform surrounding rock media by adopting an irregular hexahedron to form an optimized model; quality parameters of all units of the optimized model are checked, iterative optimization is carried out on the shapes of the units, so that transition between the units of different sizes and different types is uniform until all the units meet the quality requirements, and the method can well fit a complex structure type and is high in practicability. The discretization error of the model is reduced to a great extent; and the forward modeling precision of an actual tunnel complex environment resistivity method is improved.
Owner:SHANDONG UNIV

Biaxial rotation modulation initial fine alignment method

ActiveCN112284419AReduce time requirements for initial alignmentHigh precisionMeasurement devicesGyroscopeComputation complexity
The invention provides a biaxial rotation modulation initial fine alignment method. The method comprises the steps: acquiring the latitude and elevation information of the position where the carrier is located, completing the coarse alignment process of the system, and executing the fine alignment process based on the navigation calculation result. The method mainly solves the problems that in thefine alignment process, due to the fact that constant zero offset of an inertial device in an error model is not completely observable, and the convergence speed is low. By introducing the double-shaft rotation modulation mechanism, an error model can be improved to meet completely observable conditions, so the precision and reliability of an alignment result are ensured. By shortening the discretization time and increasing the length of the observation sequence in unit time, richer observation information is obtained, the convergence time of the equivalent sky-oriented gyroscope constant zero offset estimation sequence is greatly shortened, and the rapidity of initial alignment is improved. By optimizing the updating method of the discretization error model, the problem that the calculation complexity is increased due to the fact that the filtering period is shortened is solved. In combination with the three parts, the patent provides a rapid and high-precision biaxial rotation modulation initial fine alignment method with high engineering practicability.
Owner:AIR FORCE UNIV PLA

Convolutional neural network architecture search method based on differentiable sampler and progressive learning

PendingCN114239795AOptimizing Probability Distribution FunctionsReduce discretization errorCharacter and pattern recognitionNeural architecturesEngineeringArtificial intelligence
Aiming at the limitation of the prior art, the invention provides a convolutional neural network architecture searching method based on a differentiable sampler and progressive learning, and the method comprises the steps: directly carrying out the sampling optimization of a constructed super network through employing the differentiable sampler; an optimization target of architecture search can be converted from optimization of a super network to search for an optimal probability distribution function, and the expectation of a loss function of a sub-network under the probability distribution is minimized; according to the method, the probability distribution function of the sub-network can be optimized by evaluating the performance of the sub-network, so that discretization errors are reduced. Meanwhile, due to the fact that a progressive learning strategy is adopted, stable search can be carried out in the search space which is increased in an index level, and therefore a more complex convolutional neural network architecture can be obtained.
Owner:GUANGDONG UNIV OF TECH

Analog filter

An analog filter comprising a first arithmetic operation section 2-1 consisting of a plurality of sets of processing circuit being cascade connected, each processing circuit having an S / H circuit of plural stages for holding a DELTA SIGMA -modulated signal and an analog adder for adding the input and output signals of the S / H circuit, in which the number of stages of the S / H circuits 11-1, 14-1, 17-1 and 20-1 decreases toward the end of cascade connection, and a second arithmetic operation section 2-2 configured in the same way, which are cascade connected. By using such an analog filter, over-sampling and convolution of a DELTA SIGMA -modulated signal are conducted so that the envelope of the filter output may be a quadratic curve of finite carrier that converges to zero at finite sampling points to prevent phase distortion of an LPF and a discretization error due to a conventional function. Compared with a conventional circuit for over-sampling and convolution, the number of stages of the S / H circuits and the number of adders are small.
Owner:酒井康江

Method for determining corrected rotational speed signal and electric motor device

The invention relates to a method and an electric motor arrangement for determining a corrected rotational speed signal. In one step of the method, a periodic rotational angle signal is detected which has a periodic rotational angle error which is dependent on the rotational angle. Converting the rotation angle signal into a digital original speed signal (16), due to the rotation angle error, the digital original speed signal has an interference ripple, and the cycle duration of the interference ripple corresponds to the cycle duration of the rotation angle error . The digital raw rotational speed signal (16) comprises a plurality of sampled values ​​(07), which are spaced apart in time by the duration of the sampling period, the half-period duration of the disturbance ripple of the raw rotational speed signal (16) being determined. Averaging at least one pair of sampling values ​​(07) of the original rotational speed signal (16), the time interval of the at least one pair of sampling values ​​aside from the time discretization error is the interference ripple of the original rotational speed signal (16) The known half-cycle duration. The average value is obtained by averaging. A correction value is formed that is dependent on the sampling period duration and the frequency of the disturbance ripple to account for discretization errors. The corrected rotational speed signal is formed from the difference between the mean value and the corrected value. The correction signal varies in a sawtooth fashion as a function of the difference between the sampling period duration and the period duration of the disturbance ripple, the maximum amplitude of the correction signal also increasing with increasing frequency of the disturbance ripple.
Owner:SCHAEFFLER TECH AG & CO KG
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