A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

A modified Hopfield model for solving the N-Queens problem

A neural network model for solving the N-Queens problem is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of the N-Queens problem. Simulation results are presented to validate the proposed approach.

A novel approach for solving constrained nonlinear optimization problems using neurofuzzy systems

A neural network model for solving constrained nonlinear optimization problems with bounded variables is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are completed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of constrained nonlinear optimization problems. A fuzzy logic controller is incorporated in the network to minimize convergence time. Simulation results are presented to validate the proposed approach.

An efficient neural approach to economic load dispatch in power systems

A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements the ability of neural networks to realize some complex nonlinear function makes them attractive for system optimization the neural networks applyed in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points the internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible quilibrium points, A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

Multidisciplinary approach for the treatment of a complicated crown-root fracture in a young patient: A case report

Crown-root fractures in permanent teeth cause esthetic and functional problems. This paper reports the case of a complicated crown-root fracture in the maxillary right central inc sor of a young patient who was treated with a multidisciplinary approach in two phases. A modified Widman flap, root canal therapy, glass fiber post cementation, and adhesive tooth fragment reattachment were performed shortly after an accident. Satisfactory esthetic and functional outcomes were obtained. However, the patient did not attend follow-up visits and returned after 7 years. During this second phase, the clinical and radiographic examination showed stability and adaptation of the fragment and good periodontal health conditions, but crown darkening and a radiolucent image associated with the root apex of the fractured tooth were also observed. The periapical lesion was surgically removed by apicoectomy, and the esthetics were recovered with a direct composite res n veneer on the traumatized tooth. (Quintessence Int 2011;42:729-735)

Nanomechanical properties of biochemically modified dentin bonded interfaces

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Semiclassical approach to black hole absorption of electromagnetic radiation emitted by a rotating charge

We consider an electric charge, minimally coupled to the Maxwell field, rotating around a Schwarzschild black hole. We investigate how much of the radiation emitted from the swirling charge is absorbed by the black hole and show that most of the photons escape to infinity. For this purpose we use the Gupta-Bleuler quantization of the electromagnetic field in the modified Feynman gauge developed in the context of quantum field theory in Schwarzschild spacetime. We obtain that the two photon polarizations contribute quite differently to the emitted power. In addition, we discuss the accurateness of the results obtained in a full general relativistic approach in comparison with the ones obtained when the electric charge is assumed to be orbiting a massive object due to a Newtonian force.

Multifractal regime transition in a modified minority game model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Inverse scattering approach for massive Thirring models with integrable type-II defects

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Approach on the Electrochemical Reactivity of Poly-L-Glutamic Acid Against Doxorubicin and Its Application in the Development of a Voltammetric Sensor

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Non-Hermitian multichannel theory of ultracold collisions modified by intense light fields tuned to the red of the trapping transition

We develop a systematic scheme to treat binary collisions between ultracold atoms in the presence of a strong laser field, tuned to the red of the trapping transition. We assume that the Rabi frequency is much less than the spacing between adjacent bound-state resonances, In this approach we neglect fine and hyperfine structures, but consider fully the three-dimensional aspects of the scattering process, up to the partial d wave. We apply the scheme to calculate the S matrix elements up to the second order in the ratio between the Rabi frequency and the laser detuning, We also obtain, fur this simplified multichannel model, the asymmetric line shapes of photoassociation spectroscopy, and the modification of the scattering length due to the light field at low, but finite, entrance kinetic energy. We emphasize that the present calculations can be generalized to treat more realistic models, and suggest how to carry out a thorough numerical comparison to this semianalytic theory. [S1050-2947(98)04902-6].

Designing a modified Hopfield network to solve an Economic Dispatch problem with nonlinear cost function

Economic Dispatch (ED) problems have recently been solved by artificial neural networks approaches. In most of these dispatch models, the cost function must be linear or quadratic. Therefore, functions that have several minimum points represent a problem to the simulation since these approaches have not accepted nonlinear cost function. Another drawback pointed out in the literature is that some of these neural approaches fail to converge efficiently towards feasible equilibrium points. This paper discusses the application of a modified Hopfield architecture for solving ED problems defined by nonlinear cost function. The internal parameters of the neural network adopted here are computed using the valid-subspace technique, which guarantees convergence to equilibrium points that represent a solution for the ED problem. Simulation results and a comparative analysis involving a 3-bus test system are presented to illustrate efficiency of the proposed approach.

Nonlinear optimization using a modified Hopfield model

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving constrained nonlinear optimization problems. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach.

A column generation approach to capacitated p-median problems

The Capacitated p-median problem (CPMP) seeks to solve the optimal location of p facilities, considering distances and capacities for the service to be given by each median. In this paper we present a column generation approach to CPMP. The identified restricted master problem optimizes the covering of 1-median clusters satisfying the capacity constraints, and new columns are generated considering knapsack subproblems. The Lagrangean/surrogate relaxation has been used recently to accelerate subgradient like methods. In this work the Lagrangean/surrogate relaxation is directly identified from the master problem dual and provides new bounds and new productive columns through a modified knapsack subproblem. The overall column generation process is accelerated, even when multiple pricing is observed. Computational tests are presented using instances taken from real data from Sao Jose dos Campos' city.

The non-adiabatic hyperspherical approach to the two-dimensional D- ion in the presence of a magnetic field

We have used the adiabatic hyperspherical approach to determine the energies and wave functions of the ground state and first excited states of a two-dimensional D- ion in the presence of a magnetic field. Using a modified hyperspherical angular variable, potential energy curves are analytically obtained, allowing an accurate determination of the energy levels of this system. Upper and lower bounds for the ground-state energy have been determined by a non-adiabatic procedure, as the purpose is to improve the accuracy of method. The results are shown to be comparable to the best variational calculations reported in the literature.