Search results for "Linear problem"
showing 10 items of 10 documents
Singular solutions to a quasilinear ODE
2005
In this paper, we prove the existence of infinitely many radial solutions having a singular behaviour at the origin for a superlinear problem of the form $-\Delta_pu=|u|^{\delta-1}u$ in $B(0,1)\setminus\{0\}\subset\mathbb R^N$,\, $u=0$ for $|x|=1$, where $N>p>1$ and $\delta>p-1$. Solutions are characterized by their nodal properties. The case $\delta+1 <\frac{Np}{N-p}$ is treated. The study of the singularity is based on some energy considerations and takes into account the classification of the behaviour of the possible solutions available in the literature. By following a shooting approach, we are able to deduce the main multiplicity result from some estimates on the rotation numbers asso…
On spline methods of approximation under L-fuzzy information
2011
This work is closely related to our previous papers on algorithms of approximation under L-fuzzy information. In the classical theory of approximation central algorithms were worked out on the basis of usual, that is crisp splines. We describe central methods for solution of linear problems with balanced L-fuzzy information and develop the concept of L-fuzzy splines.
Zur Existenz von Lösungen gewisser Randwertaufgaben
1971
With the aid of some known results about integral equations of the Hammerstein type there is proofed an existence theorem for the following class of boundary value problems−y″−l 2 y′=f(x,y),y(a)=y(b)=0,l 2>0 mit|f(x, y)|=0,l 3 (x)>0. The existence range is determined by the greatest eigenvalue of some linear problem.
An Operator Splitting Method for Pricing American Options
2008
Pricing American options using partial (integro-)differential equation based methods leads to linear complementarity problems (LCPs). The numerical solution of these problems resulting from the Black-Scholes model, Kou’s jump-diffusion model, and Heston’s stochastic volatility model are considered. The finite difference discretization is described. The solutions of the discrete LCPs are approximated using an operator splitting method which separates the linear problem and the early exercise constraint to two fractional steps. The numerical experiments demonstrate that the prices of options can be computed in a few milliseconds on a PC.
Periodic and Chaotic Orbits of a Neuron Model
2015
In this paper we study a class of difference equations which describes a discrete version of a single neuron model. We consider a generalization of the original McCulloch-Pitts model that has two thresholds. Periodic orbits are investigated accordingly to the different range of parameters. For some parameters sufficient conditions for periodic orbits of arbitrary periods have been obtained. We conclude that there exist values of parameters such that the function in the model has chaotic orbits. Models with chaotic orbits are not predictable in long-term.
Mixed heuristic-non linear optimization of energy management for hydrogen storage-based multi carrier hubs
2014
In this paper, an heuristic and non-linear programming based algorithm to optimally operate an energy hub plant is proposed. The energy hub plant described in this work is the test system for the European INGRID research project. The Energy Management System defines the optimal energy flows dispatch in order to obtain the energy balance and the maximum profit for the owner of the plant. The problem is highly constrained and non-linear, for this reason the methodology cannot rely on Linear Programming (LP) methods. The Energy Management System manages two energy carriers, electricity and hydrogen, interfacing three distribution networks: the electricity, the hydrogen and the methane networks…
Simultaneous zonation and calibration of pipe network parameters
2003
A procedure for simultaneously zoning and calibrating pipe network parameters is proposed and applied to the determination of pipe resistance coefficients. The methodology is aimed at grouping the parameters of all the pipes into a small number of zone parameters, constrained to keep the difference between the computed and the measured water heads below a given tolerance. It is shown that, in the case of nonlooped networks, the methodology leads to a linear minimization problem where the objective function is a measure of the heterogeneity of the estimated parameters. In the case of looped networks an iterative procedure, where the linear problem is coupled with a nonlinear problem having a…
Avoiding strange attractors in efficient parametric families of iterative methods for solving nonlinear problems
2019
[EN] Searching zeros of nonlinear functions often employs iterative procedures. In this paper, we construct several families of iterative methods with memory from one without memory, that is, we have increased the order of convergence without adding new functional evaluations. The main aim of this manuscript yields in the advantage that the use of real multidimensional dynamics gives us to decide among the different classes designed and, afterwards, to select its most stable members. Moreover, we have found some elements of the family whose behavior includes strange attractors of different kinds that must be avoided in practice. In this sense, Feigenbaum diagrams have resulted an extremely …
Periodic orbits of single neuron models with internal decay rate 0 < β ≤ 1
2013
In this paper we consider a discrete dynamical system x n+1=βx n – g(x n ), n=0,1,..., arising as a discrete-time network of a single neuron, where 0 < β ≤ 1 is an internal decay rate, g is a signal function. A great deal of work has been done when the signal function is a sigmoid function. However, a signal function of McCulloch-Pitts nonlinearity described with a piecewise constant function is also useful in the modelling of neural networks. We investigate a more complicated step signal function (function that is similar to the sigmoid function) and we will prove some results about the periodicity of solutions of the considered difference equation. These results show the complexity of …
A posteriori error identities for nonlinear variational problems
2015
A posteriori error estimation methods are usually developed in the context of upper and lower bounds of errors. In this paper, we are concerned with a posteriori analysis in terms of identities, i.e., we deduce error relations, which holds as equalities. We discuss a general form of error identities for a wide class of convex variational problems. The left hand sides of these identities can be considered as certain measures of errors (expressed in terms of primal/dual solutions and respective approximations) while the right hand sides contain only known approximations. Finally, we consider several examples and show that in some simple cases these identities lead to generalized forms of the …