87 resultados para Single accelerator systems


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This paper investigates the learning of a wide class of single-hidden-layer feedforward neural networks (SLFNs) with two sets of adjustable parameters, i.e., the nonlinear parameters in the hidden nodes and the linear output weights. The main objective is to both speed up the convergence of second-order learning algorithms such as Levenberg-Marquardt (LM), as well as to improve the network performance. This is achieved here by reducing the dimension of the solution space and by introducing a new Jacobian matrix. Unlike conventional supervised learning methods which optimize these two sets of parameters simultaneously, the linear output weights are first converted into dependent parameters, thereby removing the need for their explicit computation. Consequently, the neural network (NN) learning is performed over a solution space of reduced dimension. A new Jacobian matrix is then proposed for use with the popular second-order learning methods in order to achieve a more accurate approximation of the cost function. The efficacy of the proposed method is shown through an analysis of the computational complexity and by presenting simulation results from four different examples.

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Thin lamellae were cut from bulk single crystal BaTiO3 using a Focused Ion Beam Microscope. They were then removed and transferred onto single crystal MgO substrates, so that their functional properties could be measured independent of the original host bulk ferroelectric. The temperature dependence of the capacitance of these isolated single crystal films was found to be strongly bulk-like, demonstrating a sharp Curie anomaly, as well as Curie-Weiss behaviour. In addition, the sudden change in the remanent polarisation as a function of temperature at TC was characteristic of a first order phase change. The work represents a dramatic improvement on that previously published by M. M. Saad, P. Baxter, R. M. Bowman, J. M. Gregg, F. D. Morrison & J. F. Scott, J. Phys: Cond. Matt., 16 L451-L456 (2004), as critical shortcomings in the original specimen geometry, involving potential signal contributions from bulk BaTiO3, have now been obviated. That the functional properties of single crystal thin film lamellae are comparable to bulk, and not like those of conventionally deposited heteroegenous thin film systems, has therefore been confirmed.

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This paper presents the design of a novel single chip adaptive beamformer capable of performing 50 Gflops, (Giga-floating-point operations/second). The core processor is a QR array implemented on a fully efficient linear systolic architecture, derived using a mapping that allows individual processors for boundary and internal cell operations. In addition, the paper highlights a number of rapid design techniques that have been used to realise this system. These include an architecture synthesis tool for quickly developing the circuit architecture and the utilisation of a library of parameterisable silicon intellectual property (IP) cores, to rapidly develop detailed silicon designs.

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This letter derives mathematical expressions for the received signal-to-interference-plus-noise ratio (SINR) of uplink Single Carrier (SC) Frequency Division Multiple Access (FDMA) multiuser MIMO systems. An improved frequency domain receiver algorithm is derived for the studied systems, and is shown to be significantly superior to the conventional linear MMSE based receiver in terms of SINR and bit error rate (BER) performance.

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Many-electron systems confined to a quasi-one-dimensional geometry by a cylindrical distribution of positive charge have been investigated by density functional computations in the unrestricted local spin density approximation. Our investigations have been focused on the low-density regime, in which electrons are localized. The results reveal a wide variety of different charge and spin configurations, including linear and zig-zag chains, single-and double-strand helices, and twisted chains of dimers. The spin-spin coupling turns from weakly antiferromagnetic at relatively high density, to weakly ferromagnetic at the lowest densities considered in our computations. The stability of linear chains of localized charge has been investigated by analyzing the radial dependence of the self-consistent potential and by computing the dispersion relation of low-energy harmonic excitations.

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This paper studies the ergodic capacity of multiple-input multiple-output (MIMO) systems with a single co-channel interferer in the low signal-to-noise-ratio (SNR) regime. Two MIMO models namely Rician and Rayleigh-product channels are investigated. Exact analytical expressions for the minimum energy per information bit, Eb/N0min, and wideband slope, S0, are derived for both channels. Our results show that the minimum energy per information bit is the same for both channels while their wideband slopes differ significantly. Further, the impact of the numbers of transmit and receive antennas, the Rician K factor, the channel mean matrix and the interference-to-noise-ratio (INR) on the capacity, is addressed. Results indicate that interference degrades the capacity by increasing the required minimum energy per information bit and reducing the wideband slope. Simulation results validate our analytical results.

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A theory of strongly interacting Fermi systems of a few particles is developed. At high excit at ion energies (a few times the single-parti cle level spacing) these systems are characterized by an extreme degree of complexity due to strong mixing of the shell-model-based many-part icle basis st at es by the residual two- body interaction. This regime can be described as many-body quantum chaos. Practically, it occurs when the excitation energy of the system is greater than a few single-particle level spacings near the Fermi energy. Physical examples of such systems are compound nuclei, heavy open shell atoms (e.g. rare earths) and multicharged ions, molecules, clusters and quantum dots in solids. The main quantity of the theory is the strength function which describes spreading of the eigenstates over many-part icle basis states (determinants) constructed using the shell-model orbital basis. A nonlinear equation for the strength function is derived, which enables one to describe the eigenstates without diagonalization of the Hamiltonian matrix. We show how to use this approach to calculate mean orbital occupation numbers and matrix elements between chaotic eigenstates and introduce typically statistical variable s such as t emperature in an isolated microscopic Fermi system of a few particles.

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The use of accelerators, with compute architectures different and distinct from the CPU, has become a new research frontier in high-performance computing over the past ?ve years. This paper is a case study on how the instruction-level parallelism offered by three accelerator technologies, FPGA, GPU and ClearSpeed, can be exploited in atomic physics. The algorithm studied is the evaluation of two electron integrals, using direct numerical quadrature, a task that arises in the study of intermediate energy electron scattering by hydrogen atoms. The results of our ‘productivity’ study show that while each accelerator is viable, there are considerable differences in the implementation strategies that must be followed on each.

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This paper arose from the work carried out for the Cullen/Uff Joint Inquiry into Train Protection Systems. It is concerned with the problem of evaluating the benefits of safety enhancements in order to avoid rare, but catastrophic accidents, and the role of Operations Research in the process. The problems include both input values and representation of outcomes. A key input is the value of life. This paper briefly discusses why the value of life might vary from incident to incident and reviews alternative estimates before producing a 'best estimate' for rail. When the occurrence of an event is uncertain, the normal method is to apply a single 'expected' value. This paper argues that a more effective method of representing such situations is through Monte-Carlo simulation and demonstrates the use of the methodology on a case study of the decision as to whether or not advanced train protection (ATP) should have been installed on a route to the west of London. This paper suggests that the output is more informative than traditional cost-benefit appraisals or engineering event tree approaches. It also shows that, unlike the results from utilizing the traditional approach, the value of ATP on this route would be positive over 50% of the time.

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Neotropical orchid bees (Euglossini) are conspicuously different from other corbiculate bees (Apinae) in their lack of advanced sociality and in male use of acquired odors (fragrances) as pheromone-analogues. In both contexts, orchid bee mating systems, in particular the number of males a female mates with, are of great interest but are currently unknown. To assess female mating frequency in the genus Euglossa, we obtained nests from three species in Mexico and Panama and genotyped mothers and their brood at microsatellite DNA loci. In 26 out of 29 nests, genotypes of female brood were fully consistent with being descended from a singly mated mother. In nests with more than one adult female present, those adult females were frequently related, with genotypes being consistent with full sister-sister (r = 0.75) or mother-daughter (r = 0.5) relationships. Thus, our genetic data support the notions of female philopatry and nest-reuse in the genus Euglossa. Theoretically, single mating should promote the evolution of eusociality by maximizing the relatedness among individuals in a nest. However, in Euglossini this genetic incentive has not led to the formation of eusocial colonies as in other corbiculate bees, presumably due to differing ecological or physiological selective regimes. Finally, monandry in orchid bees is in agreement with the theory that females select a single best mate based on the male fragrance phenotype, which may contain information on male age, cognitive ability, and competitive strength.