969 resultados para Maclaurin series
Resumo:
Superconducting Fault Current Limiters (SFCLs) are able to reduce fault currents to an acceptable value, reducing potential mechanical and thermal damage and allowing more flexibility in an electric power system's design. Due to limitations in current YBCO thin film manufacturing techniques, it is necessary to connect a number of thin films in different series and parallel configurations in order to realise a practical SFCL for electric power system applications. The amount of resistance generated (i.e. the degree of current limitation), the characteristics of the S-N transition, and the time at which they operate is different depending on their comparative characteristics. However, it is desirable for series-connected thin films to have an operating time difference as small as possible to avoid placing an excess burden on certain thin films. The role of a parallel resistance, along with the influence of thin film characteristics, such as critical current (Ic), are discussed in regards to the design of SFCLs using YBCO thin films. © 2008 IOP Publishing Ltd.
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In this paper we study parameter estimation for time series with asymmetric α-stable innovations. The proposed methods use a Poisson sum series representation (PSSR) for the asymmetric α-stable noise to express the process in a conditionally Gaussian framework. That allows us to implement Bayesian parameter estimation using Markov chain Monte Carlo (MCMC) methods. We further enhance the series representation by introducing a novel approximation of the series residual terms in which we are able to characterise the mean and variance of the approximation. Simulations illustrate the proposed framework applied to linear time series, estimating the model parameter values and model order P for an autoregressive (AR(P)) model driven by asymmetric α-stable innovations. © 2012 IEEE.
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The object of this paper is to give a complete treatment of the realizability of positive-real biquadratic impedance functions by six-element series-parallel networks comprising resistors, capacitors, and inductors. This question was studied but not fully resolved in the classical electrical circuit literature. Renewed interest in this question arises in the synthesis of passive mechanical impedances. Recent work by the authors has introduced the concept of a regular positive-real functions. It was shown that five-element networks are capable of realizing all regular and some (but not all) nonregular biquadratic positive-real functions. Accordingly, the focus of this paper is on the realizability of nonregular biquadratics. It will be shown that the only six-element series-parallel networks which are capable of realizing nonregular biquadratic impedances are those with three reactive elements or four reactive elements. We identify a set of networks that can realize all the nonregular biquadratic functions for each of the two cases. The realizability conditions for the networks are expressed in terms of a canonical form for biquadratics. The nonregular realizable region for each of the networks is explicitly characterized. © 2004-2012 IEEE.
Resumo:
With series insulated-gate bipolar transistor (IGBT) operation, well-matched gate drives will not ensure balanced dynamic voltage sharing between the switching devices. Rather, it is IGBT parasitic capacitances, mainly gate-to-collector capacitance Cgc, that dominate transient voltage sharing. As Cgc is collector voltage dependant and is significantly larger during the initial turn-off transition, it dominates IGBT dynamic voltage sharing. This paper presents an active control technique for series-connected IGBTs that allows their dynamic voltage transition dV\ce/dt to adaptively vary. Both switch ON and OFF transitions are controlled to follow a predefined dVce/dt. Switching losses associated with this technique are minimized by the adaptive dv /dt control technique incorporated into the design. A detailed description of the control circuits is presented in this paper. Experimental results with up to three series devices in a single-ended dc chopper circuit, operating at various low voltage and current levels, are used to illustrate the performance of the proposed technique. © 2012 IEEE.
Resumo:
This paper presents the use of an Active Voltage Control (AVC) technique for balancing the voltages in a series connection of Insulated Gate Bipolar Transistors (IGBTs). The AVC technique can control the switching trajectory of an IGBT according to a pre-set reference signal. In series connections, every series connected IGBT follows the reference and so that the dynamic voltage sharing is achieved. For the static voltage balancing, a temporary clamp technique is introduced. The temporary clamp technique clamps the collector-emitter voltage of all the series connected IGBTs at the ideal voltage so that the IGBTs will share the voltage evenly. © 2012 IEEE.
Resumo:
Variational methods are a key component of the approximate inference and learning toolbox. These methods fill an important middle ground, retaining distributional information about uncertainty in latent variables, unlike maximum a posteriori methods (MAP), and yet generally requiring less computational time than Monte Carlo Markov Chain methods. In particular the variational Expectation Maximisation (vEM) and variational Bayes algorithms, both involving variational optimisation of a free-energy, are widely used in time-series modelling. Here, we investigate the success of vEM in simple probabilistic time-series models. First we consider the inference step of vEM, and show that a consequence of the well-known compactness property of variational inference is a failure to propagate uncertainty in time, thus limiting the usefulness of the retained distributional information. In particular, the uncertainty may appear to be smallest precisely when the approximation is poorest. Second, we consider parameter learning and analytically reveal systematic biases in the parameters found by vEM. Surprisingly, simpler variational approximations (such a mean-field) can lead to less bias than more complicated structured approximations.
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We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/.
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The accurate prediction of time-changing covariances is an important problem in the modeling of multivariate financial data. However, some of the most popular models suffer from a) overfitting problems and multiple local optima, b) failure to capture shifts in market conditions and c) large computational costs. To address these problems we introduce a novel dynamic model for time-changing covariances. Over-fitting and local optima are avoided by following a Bayesian approach instead of computing point estimates. Changes in market conditions are captured by assuming a diffusion process in parameter values, and finally computationally efficient and scalable inference is performed using particle filters. Experiments with financial data show excellent performance of the proposed method with respect to current standard models.
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This paper presents flow field measurements for the turbulent stratified burner introduced in two previous publications in which high resolution scalar measurements were made by Sweeney et al. [1,2] for model validation. The flow fields of the series of premixed and stratified methane/air flames are investigated under turbulent, globally lean conditions (φg=0.75). Velocity data acquired with laser Doppler anemometry (LDA) and particle image velocimetry (PIV) are presented and discussed. Pairwise 2-component LDA measurements provide profiles of axial velocity, radial velocity, tangential velocity and corresponding fluctuating velocities. The LDA measurements of axial and tangential velocities enable the swirl number to be evaluated and the degree of swirl characterized. Power spectral density and autocorrelation functions derived from the LDA data acquired at 10kHz are optimized to calculate the integral time scales. Flow patterns are obtained using a 2-component PIV system operated at 7Hz. Velocity profiles and spatial correlations derived from the PIV and LDA measurements are shown to be in very good agreement, thus offering 3D mapping of the velocities. A strong correlation was observed between the shape of the recirculation zones above the central bluff body and the effects of heat release, stoichiometry and swirl. Detailed analyses of the LDA data further demonstrate that the flow behavior changes significantly with the levels of swirl and stratification, which combines the contributions of dilatation, recirculation and swirl. Key turbulence parameters are derived from the total velocity components, combining axial, radial and tangential velocities. © 2013 The Combustion Institute.
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This work applies a variety of multilinear function factorisation techniques to extract appropriate features or attributes from high dimensional multivariate time series for classification. Recently, a great deal of work has centred around designing time series classifiers using more and more complex feature extraction and machine learning schemes. This paper argues that complex learners and domain specific feature extraction schemes of this type are not necessarily needed for time series classification, as excellent classification results can be obtained by simply applying a number of existing matrix factorisation or linear projection techniques, which are simple and computationally inexpensive. We highlight this using a geometric separability measure and classification accuracies obtained though experiments on four different high dimensional multivariate time series datasets. © 2013 IEEE.
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A gain measurement technique, based on Fourier series expansion of periodically extended single fringe of the amplified spontaneous emission spectrum, is proposed for Fabry-Perot semiconductor lasers. The underestimation of gain due to the limited resolution of the measurement system is corrected by a factor related to the system response function. The standard deviations of the gain-reflectivity product under low noise conditions are analyzed for the Fourier series expansion method and compared with those of the Hakki-Paoli method and Cassidy's method. The results show that the Fourier series expansion method is the least sensitive to noise among the three methods. The experiment results obtained by the three methods are also presented and compared.
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An electro-optic variable optical attenuator in silicon-on-insulator is designed and fabricated. A series Structure is used to improve the device efficiency Compared to the attenuator in the single p-i-n diode Structure in the same modulating length, the attenuation range of the device in the series structure improves 2-3 times in the same injecting current density, while the insertion loss is not affected. The maximum dynamic attenuation of the device is greater than 30 dB. The response frequency is obtained to be about 2 MHz.
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Within the Buttiker dephasing model, the backscattering in the dephasing process is eliminated by setting a proper boundary condition. Explicit expression is carried out for the effective total tunneling probability in the presence of multiple pure dephasing scatterers with partial coherence. The derived formula is illustrated analytically by various limiting cases, and numerically for its application in tunneling through multibarrier systems.
Resumo:
We presented a series of symmetric double crystal X-ray diffraction (DCXD) measurements, (0 0 4), (2 2 0) and (2 - 2 0) diffraction, to investigate the strain relaxation in an InAs film grown on a GaAs(0 0 1) substrate. The strain tensor and rotation tensor were calculated according to the DCXD results. It is found that the misfit strain is relaxed nearly completely and the strain relaxation caused a triclinic deformation in the epilayer. The lattice parameter along the [1 1 0] direction is a little longer than that along the [1 - 1 0] direction. Furthermore, a significant tilt, 0.2 degrees, towards the [1 1 0] direction while a very slight one: 0.002 degrees, towards [1 - 1 0] direction were discussed. This anisotropic strain relaxation is attributed to the asymmetric distribution of misfit dislocations, which is also indicated by the variation of the full-width at half-maximum (FWHM) of (0 0 4) diffraction along four azimuth angles. (C) 1998 Elsevier Science B.V. All rights reserved.