By applying the real representation matrix and the Moore-Penrose inverse of the split quaternion matrix, we first study the split quaternion least squares problem with equality constraint (SQLSE) and obtain its genera...
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By applying the real representation matrix and the Moore-Penrose inverse of the split quaternion matrix, we first study the split quaternion least squares problem with equality constraint (SQLSE) and obtain its general solution and minimum norm solution. Then, we obtain the Karush-Kuhn-Tucker equation, which is an equivalent problem of the SQLSE problem. Immediately after, we propose a numerical algorithm on the real number field for the minimum norm solution of the SQLSE problem and enumerate three examples to display its validity. Eventually, we provide an application of the SQLSE problem in the color image restoration.
Unlike the continuous relaxation spectrum (CRS), discrete relaxation spectra (DRS) are nonunique. This means that the linear viscoelastic response of a material can be described by two or more distinct DRS. Constraint...
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Unlike the continuous relaxation spectrum (CRS), discrete relaxation spectra (DRS) are nonunique. This means that the linear viscoelastic response of a material can be described by two or more distinct DRS. Constraints like parsimony and consistency help us to infer meaningful DRS, but are not sufficient to induce uniqueness as it is an inherent property of discretization. Using parsimonious DRS from two different programs (DISCRETE and pyReSpect) on data drawn from experiments, simulations, and theory, we demonstrate that nonuniqueness does not hinder the two most common applications of relaxation spectra, viz. characterization and interconversion. Furthermore, information for reconstructing the CRS underlying the data is embedded in the DRS. Therefore, for most practical considerations, we find that the nonuniqueness of the DRS does not matter.
This paper explores the effectiveness of the Lie derivative discretisation scheme applied to two particular types of nonlinear dynamical equations, both of which have the characteristic of time variables in the denomi...
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This paper explores the effectiveness of the Lie derivative discretisation scheme applied to two particular types of nonlinear dynamical equations, both of which have the characteristic of time variables in the denominator position. The discrete structure of non-autonomous systems is established. In particular, we exclude time variables as state variables to prevent non-autonomous systems from becoming autonomous systems. Using this method, we compute the numerical solution of the system above and compare it with the precise solution and the numerical findings of Runge-Kutta, demonstrating the broad applicability of the Lie derivative numerical algorithm. Finally, we determine the CPU consumption time of two numerical algorithms, thus providing evidence of the high efficiency of the Lie derivative numerical algorithm.
In this paper, a theoretical model of the contact characteristics for layers on irregular surfaces is established by analyzing the contact deformation and slip ratio at the placement path points. Based on this model, ...
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In this paper, a theoretical model of the contact characteristics for layers on irregular surfaces is established by analyzing the contact deformation and slip ratio at the placement path points. Based on this model, a numerical algorithm for calculating the contact characteristics at any path point is proposed. The normal stress field, tangential stress field, and contact status of the contact area at four path points on the double-curved surface mold are obtained using the algorithm and verified through experiments. The results indicate that the model can be used to predict the contact characteristics at any placement path point, and the possible defects at points P3 and P4 are initially identified by analyzing the contact characteristics. In addition, compared to the 8-h computational time required for simulation calculation, this numerical algorithm takes only 20 ms to compute, which shows that the developed model has greatly reduced the calculation time.
In this work, we address three non-convex optimization problems associated with the training of shallow neural networks (NNs) for exact and approximate representation, as well as for regression tasks. Through a mean-f...
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In this work, we address three non-convex optimization problems associated with the training of shallow neural networks (NNs) for exact and approximate representation, as well as for regression tasks. Through a mean-field approach, we convexify these problems and, applying a representer theorem, prove the absence of relaxation gaps. We establish generalization bounds for the resulting NN solutions, assessing their predictive performance on test datasets, analyzing the impact of key hyperparameters on these bounds, and proposing optimal choices. On the computational side, we examine the discretization of the convexified problems and derive convergence rates. For low-dimensional datasets, these discretized problems are efficiently solvable using the simplex method. For high-dimensional datasets, we propose a sparsification algorithm that, combined with gradient descent for over-parameterized shallow NNs, yields effective solutions to the primal problems.
We present a stochastic method for the simulation of Laplace's equation with a mixed boundary condition in planar domains that are polygonal or bounded by circular arcs. We call this method the Reflected Walk-on-S...
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We present a stochastic method for the simulation of Laplace's equation with a mixed boundary condition in planar domains that are polygonal or bounded by circular arcs. We call this method the Reflected Walk-on-Spheres algorithm. The method combines a traditional Walk-on- Spheres algorithm with use of reflections at the Neumann boundaries. We apply our algorithm to simulate numerical conformal mappings from certain quadrilaterals to the corresponding canonical domains, and to compute their conformal moduli. Finally, we give examples of the method on three dimensional polyhedral domains, and use it to simulate the heat flow on an Lshaped insulated polyhedron.
The aim of the work is to provide a mathematical description of the lubricant's behavior model used in sliding bearings of bridge structures. It was previously established that the Maxwell model does not correctly...
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The aim of the work is to provide a mathematical description of the lubricant's behavior model used in sliding bearings of bridge structures. It was previously established that the Maxwell model does not correctly describe the lubricant's behavior in a wide range of temperatures and deformation rates. The lubricant model should take into account not only viscosity but also plasticity. The Anand model, which was adapted by introducing temperature dependencies for a number of material parameters, was chosen to describe the lubricant behavior. The functionality of the previously created procedure for identifying material properties was also expanded on the modified Anand model. This made it possible to obtain a lubricant mathematical model with an error of less than 5% in the operating temperature range from -40 to +80 degrees C. The study included a description of the behavior model for two lubricants: CIATIM-221 and CIATIM-221F. CIATIM-221F differs from CIATIM-221 by including superfine particles of polytetrafluoroethylene (PTFE) to improve properties. The study confirmed that the modified Anand model allows describing the material behavior more accurately than the Maxwell model. It was found that the samples behave as a solid over the entire temperature range (from -40 to +80 degrees C). A comparative analysis of the thermal behavior of CIATIM-221 and CIATIM-221F was performed.
This work utilises a fractal-fractional operator to examine the dynamics of transmission of measles disease. The existence and uniqueness of the measles model have been thoroughly examined in the context of the fixed ...
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This work utilises a fractal-fractional operator to examine the dynamics of transmission of measles disease. The existence and uniqueness of the measles model have been thoroughly examined in the context of the fixed point theorem, specifically utilising the Atangana-Baleanu fractal and fractional operators. The model has been demonstrated to possess both Hyers-Ulam stability and Hyers-Ulam Rassias stability. Furthermore, a qualitative analysis of the model was performed, including examination of key parameters such as the fundamental reproduction number, the measles-free and measles-present equilibria, and assessment of global stability. This research has shown that the transmission of measles disease is affected by natural phenomena, as changes in the fractal-fractional order lead to changes in the disease dynamics. Furthermore, environmental contamination has been shown to play a significant role in the transmission of the measles disease.
We state some widely satisfied hypotheses, depending only on two functions g and h, under which the composition of a forward stable algorithm for g and a forward stable algorithm for h is a forward stable algorithm fo...
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We state some widely satisfied hypotheses, depending only on two functions g and h, under which the composition of a forward stable algorithm for g and a forward stable algorithm for h is a forward stable algorithm for the composition g ? h. We show that the failure of these conditions can potentially lead to unstable algorithms. Finally, we list a number of examples to illustrate the new concepts and the usability of the results.
As a complex uncertain differential equation, how to solve the multi-dimensional uncertain differential equation is a complicated and difficult problem. This paper will be devoted to the a-path of some special multi-d...
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As a complex uncertain differential equation, how to solve the multi-dimensional uncertain differential equation is a complicated and difficult problem. This paper will be devoted to the a-path of some special multi-dimensional uncertain differential equations, namely, multi-factor uncertain differential equations, nested uncertain differential equations and multifactor nested uncertain differential equations. The alpha psi-path method is used to study the numerical solution problems of the above three special multi-dimensional uncertain differential equations. At the same time, the inverse uncertainty distributions and expected values of these three special multi-dimensional uncertain differential equations are also obtained. At last, the numerical algorithm examples are given to verify it.
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