The condensed nearest neighbor rule using the concept of mutual nearest neighborhood (Corresp.)

A two-stage iterative algorithm for selecting a subset of a training set of samples for use in a condensed nearest neighbor (CNN) decision rule is introduced. The proposed method uses the concept of mutual nearest neighborhood for selecting samples close to the decision line. The efficacy of the algorithm is brought out by means of an example.

Elasto-plastic contact stress analysis of joints subjected to cyclic loading

Rigorous elastic-plastic finite element analysis of joints subjected to cyclic loading is carried out. An incremental-iterative algorithm is developed in a modular form combining elasto-plastic material behaviour and contact stress analysis. For the case of the interference fit, the analysis sequentially carries out insertion of the pin and application of the load on the joint, covering possible initiation of separation (and/or yielding) and progressively the receding/advancing contact at the pin-plate interface. Deformations of both the plate and the pin are considered in the analysis. Numerical examples are presented for the case of an interference fit pin in a large plate under remote cyclic tension, and for an interference fit pin lug joint subjected to cyclic loading. A detailed study is carried out for the latter problem considering the effect of change in contact/separation at the pin-plate interface on local stresses, strains and redistribution of these stresses with the spread of a plastic zone. The results of the study are a useful input for the estimation of the fatigue life of joints. Copyright (C) 1996 Elsevier Science Ltd

Maximum Margin Classifiers with Specified False Positive and False Negative Error Rates

This paper addresses the problem of maximum margin classification given the moments of class conditional densities and the false positive and false negative error rates. Using Chebyshev inequalities, the problem can be posed as a second order cone programming problem. The dual of the formulation leads to a geometric optimization problem, that of computing the distance between two ellipsoids, which is solved by an iterative algorithm. The formulation is extended to non-linear classifiers using kernel methods. The resultant classifiers are applied to the case of classification of unbalanced datasets with asymmetric costs for misclassification. Experimental results on benchmark datasets show the efficacy of the proposed method.

Design of MMSE filterbank precoder and equalizer for MIMO frequency selective channels

In this paper, we consider the problem of designing minimum mean squared error (MMSE) filterbank precoder and equalizer for multiple input multiple output (MIMO) frequency selective channels. We derive the conditions to be satisfied by the optimal precoder-equalizer pair, and provide an iterative algorithm for solving them. The optimal design is very general, in that it is not constrained by channel dimensions, channel order, channel rank, or the input constellation. We also discuss some pertinent difierences between the filterbank approach and the space-time approach to the design of optimal precoder and equalizer. Simulation results demonstrate that the proposed design performs better than the space-time systems while supporting a higher data rate.

Algorithmic approach to simulate Hamiltonian dynamics and an NMR simulation of quantum state transfer

We propose an iterative algorithm to simulate the dynamics generated by any n-qubit Hamiltonian. The simulation entails decomposing the unitary time evolution operator U (unitary) into a product of different time-step unitaries. The algorithm product-decomposes U in a chosen operator basis by identifying a certain symmetry of U that is intimately related to the number of gates in the decomposition. We illustrate the algorithm by first obtaining a polynomial decomposition in the Pauli basis of the n-qubit quantum state transfer unitary by Di Franco et al. [Phys. Rev. Lett. 101, 230502 (2008)] that transports quantum information from one end of a spin chain to the other, and then implement it in nuclear magnetic resonance to demonstrate that the decomposition is experimentally viable. We further experimentally test the resilience of the state transfer to static errors in the coupling parameters of the simulated Hamiltonian. This is done by decomposing and simulating the corresponding imperfect unitaries.

Simulation of inhomogeneous distributions of ultracold atoms in an optical lattice via a massively parallel implementation of nonequilibrium strong-coupling perturbation theory

We present a nonequilibrium strong-coupling approach to inhomogeneous systems of ultracold atoms in optical lattices. We demonstrate its application to the Mott-insulating phase of a two-dimensional Fermi-Hubbard model in the presence of a trap potential. Since the theory is formulated self-consistently, the numerical implementation relies on a massively parallel evaluation of the self-energy and the Green's function at each lattice site, employing thousands of CPUs. While the computation of the self-energy is straightforward to parallelize, the evaluation of the Green's function requires the inversion of a large sparse 10(d) x 10(d) matrix, with d > 6. As a crucial ingredient, our solution heavily relies on the smallness of the hopping as compared to the interaction strength and yields a widely scalable realization of a rapidly converging iterative algorithm which evaluates all elements of the Green's function. Results are validated by comparing with the homogeneous case via the local-density approximation. These calculations also show that the local-density approximation is valid in nonequilibrium setups without mass transport.

Exploring isospectral cantilever beams using electromagnetism inspired optimization technique

Isospectral beams have identical free vibration frequency spectrum for a specific boundary condition. The problem of finding non-uniform beams which are isospectral to a given uniform beam, with fixed-free boundary condition, leads to a multimodal optimization problem. The first Q natural frequencies of the given uniform Euler-Bernoulli beam are determined using analytical solution. The first Q natural frequencies of a non-uniform beam are obtained with the help of finite element modeling. In order to obtain the non-uniform beams isospectral to a given uniform beam, an error function is designed, which calculates the difference between the spectra of the given uniform beam and the non-uniform beam. In our study, this error function is minimized using electromagnetism inspired optimization technique, a population based iterative algorithm inspired by the attraction-repulsion physics of electromagnetism. Numerical results show the existence of the isospectral non-uniform beams for a given uniform beam, which occur as local minima. Non-uniform beams isospectral to a damaged beam, are also explored using the proposed methodology to illustrate the fact that accurate structural damage identification is difficult by just frequency measurements. (C) 2012 Elsevier B.V. All rights reserved.

QEP Based Solution for Power Allocation in Amplify and Forward Networks

The problem of cooperative beamforming for maximizing the achievable data rate of an energy constrained two-hop amplify-and-forward (AF) network is considered. Assuming perfect channel state information (CSI) of all the nodes, we evaluate the optimal scaling factor for the relay nodes. Along with individual power constraint on each of the relay nodes, we consider a weighted sum power constraint. The proposed iterative algorithm initially solves a set of relaxed problems with weighted sum power constraint and then updates the solution to accommodate individual constraints. These relaxed problems in turn are solved using a sequence of Quadratic Eigenvalue Problems (QEP). The key contribution of this letter is the generalization of cooperative beamforming to incorporate both the individual and weighted sum constraint. Furthermore, we have proposed a novel algorithm based on Quadratic Eigenvalue Problem (QEP) and discussed its convergence.

Image deconvolution using a Gaussian scale mixtures model to approximate the wavelet sparseness constraint

This paper proposes to use an extended Gaussian Scale Mixtures (GSM) model instead of the conventional ℓ1 norm to approximate the sparseness constraint in the wavelet domain. We combine this new constraint with subband-dependent minimization to formulate an iterative algorithm on two shift-invariant wavelet transforms, the Shannon wavelet transform and dual-tree complex wavelet transform (DTCWT). This extented GSM model introduces spatially varying information into the deconvolution process and thus enables the algorithm to achieve better results with fewer iterations in our experiments. ©2009 IEEE.

Measurements of Flow Patterns and Velocities of Gas -Water Two -Phase Flows Using Electrical Resistance Imaging

This paper presents a measurement of flow patterns and flow velocities of gas-water two-phase flows based on the technique of electrical resistance tomography (ERT) in a 40m horizontal flow loop. A single-plane and dual-plane ERT sensor on conductive ring technique were used to gather sufficient information for the implementation of flow characteristics particularly flow pattern recognition and air cavity velocity measurement. A fast data collection strategy was applied to the dual-plane ERT sensor and an iterative algorithm was used for image reconstruction. Results, in respect to flow patterns and velocity maps, are reported.

Implementação paralela do algoritmo iterativo de busca do parâmetro de regularização ótimo para o funcional de Tikhonov no problema de restauração de imagens

O uso de técnicas com o funcional de Tikhonov em processamento de imagens tem sido amplamente usado nos últimos anos. A ideia básica nesse processo é modificar uma imagem inicial via equação de convolução e encontrar um parâmetro que minimize esse funcional afim de obter uma aproximação da imagem original. Porém, um problema típico neste método consiste na seleção do parâmetro de regularização adequado para o compromisso entre a acurácia e a estabilidade da solução. Um método desenvolvido por pesquisadores do IPRJ e UFRJ, atuantes na área de problemas inversos, consiste em minimizar um funcional de resíduos através do parâmetro de regularização de Tikhonov. Uma estratégia que emprega a busca iterativa deste parâmetro visando obter um valor mínimo para o funcional na iteração seguinte foi adotada recentemente em um algoritmo serial de restauração. Porém, o custo computacional é um fator problema encontrado ao empregar o método iterativo de busca. Com esta abordagem, neste trabalho é feita uma implementação em linguagem C++ que emprega técnicas de computação paralela usando MPI (Message Passing Interface) para a estratégia de minimização do funcional com o método de busca iterativa, reduzindo assim, o tempo de execução requerido pelo algoritmo. Uma versão modificada do método de Jacobi é considerada em duas versões do algoritmo, uma serial e outra em paralelo. Este algoritmo é adequado para implementação paralela por não possuir dependências de dados como de Gauss-Seidel que também é mostrado a convergir. Como indicador de desempenho para avaliação do algoritmo de restauração, além das medidas tradicionais, uma nova métrica que se baseia em critérios subjetivos denominada IWMSE (Information Weighted Mean Square Error) é empregada. Essas métricas foram introduzidas no programa serial de processamento de imagens e permitem fazer a análise da restauração a cada passo de iteração. Os resultados obtidos através das duas versões possibilitou verificar a aceleração e a eficiência da implementação paralela. A método de paralelismo apresentou resultados satisfatórios em um menor tempo de processamento e com desempenho aceitável.

Computer simulation of reactive extrusion processes for free radical polymerization

The reactive extrusion for polymerization is an integrated polymer processing technology. A new semi-implicit iterative algorithm was proposed to deal with the complicated relationships among the chemical reaction, the macromolecular structure and the chemorheological property. Then the numerical computation expressions of the average molecular weight, the monomer conversion, and the initiator concentration were deduced, and the computer simulation of the reactive extrusion process for free radical polymerization was carried out, on basis of which reactive processing conditions can be optimized.

Study on reactive extrusion processes of block copolymer

The anionic copolymerization process of styrene-buradiene (S/B) block copolymer in a closely intermeshing co-rotating twin screw extruder with butyl-lithium initiator was studied. According to the anionic copolymerization mechanism and the reactive extrusion characteristics, the mathematical models of monomer conversion, average molecular weight and fluid viscosity during the anionic copolymerization of S/B were constructed, and then the reactive extrusion process was simulated by means of the finite volume method and the uncoupled semi-implicit iterative algorithm. Finally, the influence of the feeding mixture composition on conversion was discussed. The simulated results were nearly in agreement with the experimental results.

Free radical grafting of polyethylene with vinyl monomers by reactive extrusion

The free radical grafting of polyethylene with vinyl monomers by reactive extrusion was studied numerically. Numerical computation expressions of key variables, such as the concentrations of the initiator and polymer, grafting degree, average molecular weight and apparent viscosity, were deduced. The evolutions of the above variables were predicted by means of an uncoupled semi-implicit iterative algorithm. The monomer conversion monotonically increases with decreasing throughput or increasing initial initiator concentration; with increasing barrel temperature, the monomer conversion first increases then decreases. The simulated results are nearly in good agreement with the experimental results.

基于扰动方法的广义最佳鉴别矢量集求解的一种迭代算法

本文对广义最佳鉴别矢量的求解方法进行研究 ,根据矩阵的扰动理论 ,改进了郭提出的求解广义最佳鉴别矢量的一种迭代算法 ,提出了求解广义最佳鉴别矢量的一种新的迭代算法 .本文算法的一个突出优点是随着类别数目的增加 ,计算时间反而缩短 ;而老算法随着类别数目的增加计算时间随着增加 ;不仅如此 ,新算法的识别率不劣于老算法 .在 ORL人脸数据库的数值实验 ,验证了上述论断的正确性