163 resultados para iterative methods


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The paper present a spectral iteration technique for the analysis of linear arrays of unequally spaced dipoles of unequal lengths. As an example, the Yagi-Uda array is considered for illustration. Analysis is carried out in both the spatial as well as the spectral domains, the two being linked by the Fourier transform. The fast Fourier transform algorithm is employed to obtain an iterative solution to the electric field integral equation and the need for matrix inversion is circumvented. This technique also provides a convenient means for testing the satisfaction of the boundary conditions on the array elements. Numerical comparison of the input impedance and radiation pattern have been made with results deduced elsewhere by other methods. The computational efficency of this technique has been found to be significant for large arrays.

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Non-stationary signal modeling is a well addressed problem in the literature. Many methods have been proposed to model non-stationary signals such as time varying linear prediction and AM-FM modeling, the later being more popular. Estimation techniques to determine the AM-FM components of narrow-band signal, such as Hilbert transform, DESA1, DESA2, auditory processing approach, ZC approach, etc., are prevalent but their robustness to noise is not clearly addressed in the literature. This is critical for most practical applications, such as in communications. We explore the robustness of different AM-FM estimators in the presence of white Gaussian noise. Also, we have proposed three new methods for IF estimation based on non-uniform samples of the signal and multi-resolution analysis. Experimental results show that ZC based methods give better results than the popular methods such as DESA in clean condition as well as noisy condition.

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For the problem of speaker adaptation in speech recognition, the performance depends on the availability of adaptation data. In this paper, we have compared several existing speaker adaptation methods, viz. maximum likelihood linear regression (MLLR), eigenvoice (EV), eigenspace-based MLLR (EMLLR), segmental eigenvoice (SEV) and hierarchical eigenvoice (HEV) based methods. We also develop a new method by modifying the existing HEV method for achieving further performance improvement in a limited available data scenario. In the sense of availability of adaptation data, the new modified HEV (MHEV) method is shown to perform better than all the existing methods throughout the range of operation except the case of MLLR at the availability of more adaptation data.

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Fundamental investigations in ultrasonics in India date back to the early 20th century. But, fundamental and applied research in the field of nondestructive evaluation (NDE) came much later. In the last four decades it has grown steadily in academic institutions, national laboratories and industry. Currently, commensurate with rapid industrial growth and realisation of the benefits of NDE, the activity is becoming much stronger, deeper, broader and very wide spread. Acoustic Emission (AE) is a recent entry into the field of nondestructive evaluation. Pioneering efforts in India in AE were carried out at the Indian Institute of Science in the early 1970s. The nuclear industry was the first to utilise it. Current activity in AE in the country spans materials research, incipient failure detection, integrity evaluation of structures, fracture mechanics studies and rock mechanics. In this paper, we attempt to project the current scenario in ultrasonics and acoustic emission research in India.

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Abstract is not available.

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The paper describes a Simultaneous Implicit (SI) approach for transient stability simulations based on an iterative technique using traingularised admittance matrix [1]. The reduced saliency of generator in the subtransient state is taken advantage of to speed up the algorithm. Accordingly, generator differential equations, except rotor swing, contain voltage proportional to fluxes in the main field, dampers and a hypothetical winding representing deep flowing eddy currents, as state variables. The simulation results are validated by comparison with two independent methods viz. Runge-Kutta simulation for a simplified system and a method based on modelling damper windings using conventional induction motor theory.

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We discuss the inverse problem associated with the propagation of the field autocorrelation of light through a highly scattering object like tissue. In the first part of the work, we reconstructed the optical absorption coefficient mu(u) and particle diffusion coefficient D-B from simulated measurements which are integrals of a quantity computed from the measured intensity and intensity autocorrelation g(2)(tau) at the boundary. In the second part we recover the mean square displacement (MSD) distribution of particles in an inhomogeneous object from the sampled g(2)(tau) measure on the boundary. From the MSD, we compute the storage and loss moduli distributions in the object. We have devised computationally easy methods to construct the sensitivity matrices which are used in the iterative reconstruction algorithms for recovering these parameters from the measurements. The results of the reconstruction of mu(a), D-B, MSD and the viscoelastic parameters, which are presented, show reasonable good position and quantitative accuracy.

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The importance of interlaminar stresses has prompted a fresh look at the theory of laminated plates. An important feature in modelling such laminates is the need to provide for continuity of some strains and stresses, while at the same time allowing for the discontinuities in the others. A new modelling possibility is examined in this paper. The procedure allows for discontinuities in the in-plane stresses and transverse strains and continuity in the in-plane strains and transverse stresses. This theory is in the form of a heirarchy of formulations each representing an iterative step. Application of the theory is illustrated by considering the example of an infinite laminated strip subjected to sinusoidal loading.

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A comprehensive set of new configurations for the holographic simulation of a wide variety of mirrors is described. These holographically simulated mirrors (HSMs) have been experimentally realized and their imaging performance has been studied.

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Much progress in nanoscience and nanotechnology has been made in the past few years thanks to the increased availability of sophisticated physical methods to characterize nanomaterials. These techniques include electron microscopy and scanning probe microscopies, in addition to standard techniques such as X-ray and neutron diffraction, X-ray scattering, and various spectroscopies. Characterization of nanomaterials includes the determination not only of size and shape, but also of the atomic and electronic structures and other important properties. In this article we describe some of the important methods employed for characterization of nanostructures, describing a few case studies for illustrative purposes. These case studies include characterizations of Au, ReO3, and GaN nanocrystals; ZnO, Ni, and Co nanowires; inorganic and carbon nanotubes; and two-dimensional graphene.

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Combustion is a complex phenomena involving a multiplicity of variables. Some important variables measured in flame tests follow [1]. In order to characterize ignition, such related parameters as ignition time, ease of ignition, flash ignition temperature, and self-ignition temperature are measured. For studying the propagation of the flame, parameters such as distance burned or charred, area of flame spread, time of flame spread, burning rate, charred or melted area, and fire endurance are measured. Smoke characteristics are studied by determining such parameters as specific optical density, maximum specific optical density, time of occurrence of the densities, maximum rate of density increase, visual obscuration time, and smoke obscuration index. In addition to the above variables, there are a number of specific properties of the combustible system which could be measured. These are soot formation, toxicity of combustion gases, heat of combustion, dripping phenomena during the burning of thermoplastics, afterglow, flame intensity, fuel contribution, visual characteristics, limiting oxygen concentration (OI), products of pyrolysis and combustion, and so forth. A multitude of flammability tests measuring one or more of these properties have been developed [2]. Admittedly, no one small scale test is adequate to mimic or assess the performance of a plastic in a real fire situation. The conditions are much too complicated [3, 4]. Some conceptual problems associated with flammability testing of polymers have been reviewed [5, 6].

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Identification of the optimum generation schedule by various methods of coordinating incremental generation costs and incremental transmission losses has been described previously in the literature. This paper presents an analytical approach which reduces the time-consuming iterative procedure into a mere positive-root determination of a third-order polynomial in λ. This approach includes the effect of transmission losses and is suitable for systems with any number of plants. The validity and effectiveness of this method are demonstrated by analysing a sample system.

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Presented in the paper are the details of a method for obtaining aerodynamic characteristics of pretensioned elastic membrane rectangular sailwings. This is a nonlinear problem governed by the membrane equation for the inflated sail and the lifting surface theory integral equation for aerodynamic loads on the sail. Assuming an admissible mode shape for the inflated elastic sail, an iterative procedure based on a doublet lattice method is employed to determine the inflated configuration as well as various aerodynamic characteristics. Application of the method is made to a typical nylon-cotton sailwing of AR = 6.0 and results are presented graphically to show the effect of various parameters. The results are found to tend to plane wing values when the pretensions are large in magnitude.

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We compare two popular methods for estimating the power spectrum from short data windows, namely the adaptive multivariate autoregressive (AMVAR) method and the multitaper method. By analyzing a simulated signal (embedded in a background Ornstein-Uhlenbeck noise process) we demonstrate that the AMVAR method performs better at detecting short bursts of oscillations compared to the multitaper method. However, both methods are immune to jitter in the temporal location of the signal. We also show that coherence can still be detected in noisy bivariate time series data by the AMVAR method even if the individual power spectra fail to show any peaks. Finally, using data from two monkeys performing a visuomotor pattern discrimination task, we demonstrate that the AMVAR method is better able to determine the termination of the beta oscillations when compared to the multitaper method.