On a coincidence of the differential equation with its associated equation
Miloslav Fialka (1988)
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
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Miloslav Fialka (1988)
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
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R. Pincak, J. Smotlacha, M. Pudlak (2013)
Nanoscale Systems: Mathematical Modeling, Theory and Applications
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The electronic structure of the nanocylinder is investigated. Two cases of this kind of the nanostructure are explored: the defect-free nanocylinder and the nanocylinder whose geometry is perturbed by 2 heptagonal defects lying on the opposite sides. The characteristic quantity which is of our interest is the local density of states. To calculate it, the continuum gauge field-theory model will be used. In this model, the Dirac-like equation is solved on a curved surface. This procedure...
J. M. F. Chamayou (1981)
Stochastica
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A method is presented to compute the activity of a radioactive source. The principle of the method is based on the tuning of b, the time constant of the RC circuit of the detector with l being the rate of emission of the source, using a statistical argument. The stochastical process involved refers to the distribution of the following random voltage: Vt = ∑(0 < ti ≤ t) Yi c-b(t...
Lucas Jódar Sánchez (1986)
Stochastica
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By means of the reduction of boundary value problems to algebraic ones, conditions for the existence of solutions and explicit expressions of them are obtained. These boundary value problems are related to the second order operator differential equation X + AX + AX = 0, and X = A + BX + XC. For the finite-dimensional case, computable expressions of the solutions are given.
Pierre Alquier, Xiaoyin Li, Olivier Wintenberger (2013)
Dependence Modeling
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We establish rates of convergences in statistical learning for time series forecasting. Using the PAC-Bayesian approach, slow rates of convergence √ d/n for the Gibbs estimator under the absolute loss were given in a previous work [7], where n is the sample size and d the dimension of the set of predictors. Under the same weak dependence conditions, we extend this result to any convex Lipschitz loss function. We also identify a condition on the parameter space that ensures similar rates...
Miroslav Laitoch (1988)
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
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