982 resultados para Sequential Gaussian simulation


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As System-on-Chip (SoC) designs migrate to 28nm process node and beyond, the electromagnetic (EM) co-interactions of the Chip-Package-Printed Circuit Board (PCB) becomes critical and require accurate and efficient characterization and verification. In this paper a fast, scalable, and parallelized boundary element based integral EM solutions to Maxwell equations is presented. The accuracy of the full-wave formulation, for complete EM characterization, has been validated on both canonical structures and real-world 3-D system (viz. Chip + Package + PCB). Good correlation between numerical simulation and measurement has been achieved. A few examples of the applicability of the formulation to high speed digital and analog serial interfaces on a 45nm SoC are also presented.

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Gene expression in living systems is inherently stochastic, and tends to produce varying numbers of proteins over repeated cycles of transcription and translation. In this paper, an expression is derived for the steady-state protein number distribution starting from a two-stage kinetic model of the gene expression process involving p proteins and r mRNAs. The derivation is based on an exact path integral evaluation of the joint distribution, P(p, r, t), of p and r at time t, which can be expressed in terms of the coupled Langevin equations for p and r that represent the two-stage model in continuum form. The steady-state distribution of p alone, P(p), is obtained from P(p, r, t) (a bivariate Gaussian) by integrating out the r degrees of freedom and taking the limit t -> infinity. P(p) is found to be proportional to the product of a Gaussian and a complementary error function. It provides a generally satisfactory fit to simulation data on the same two-stage process when the translational efficiency (a measure of intrinsic noise levels in the system) is relatively low; it is less successful as a model of the data when the translational efficiency (and noise levels) are high.

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In this work, possibility of simulating biological organs in realtime using the Boundary Element Method (BEM) is investigated, with specific reference to the speed and the accuracy offered by BEM. First, a Graphics Processing Unit (GPU) is used to speed up the BEM computations to achieve the realtime performance. Next, instead of the GPU, a computer cluster is used. A pig liver is the biological organ considered. Results indicate that BEM is an interesting choice for the simulation of biological organs. Although the use of BEM for the simulation of biological organs is not new, the results presented in the present study are not found elsewhere in the literature.

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This paper presents a computationally efficient model for a dc-dc boost converter, which is valid for continuous and discontinuous conduction modes; the model also incorporates significant non-idealities of the converter. Simulation of the dc-dc boost converter using an average model provides practically all the details, which are available from the simulation using the switching (instantaneous) model, except for the quantum of ripple in currents and voltages. A harmonic model of the converter can be used to evaluate the ripple quantities. This paper proposes a combined (average-cum-harmonic) model of the boost converter. The accuracy of the combined model is validated through extensive simulations and experiments. A quantitative comparison of the computation times of the average, combined and switching models are presented. The combined model is shown to be more computationally efficient than the switching model for simulation of transient and steady-state responses of the converter under various conditions.

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This paper presents a comparative evaluation of the average and switching models of a dc-dc boost converter from the point of view of real-time simulation. Both the models are used to simulate the converter in real-time on a Field Programmable Gate Array (FPGA) platform. The converter is considered to function over a wide range of operating conditions, and could do transition between continuous conduction mode (CCM) and discontinuous conduction mode (DCM). While the average model is known to be computationally efficient from the perspective of off-line simulation, the same is shown here to consume more logical resources than the switching model for real-time simulation of the dc-dc converter. Further, evaluation of the boundary condition between CCM and DCM is found to be the main reason for the increased consumption of resources by the average model.

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Impoverishment of particles, i.e. the discretely simulated sample paths of the process dynamics, poses a major obstacle in employing the particle filters for large dimensional nonlinear system identification. A known route of alleviating this impoverishment, i.e. of using an exponentially increasing ensemble size vis-a-vis the system dimension, remains computationally infeasible in most cases of practical importance. In this work, we explore the possibility of unscented transformation on Gaussian random variables, as incorporated within a scaled Gaussian sum stochastic filter, as a means of applying the nonlinear stochastic filtering theory to higher dimensional structural system identification problems. As an additional strategy to reconcile the evolving process dynamics with the observation history, the proposed filtering scheme also modifies the process model via the incorporation of gain-weighted innovation terms. The reported numerical work on the identification of structural dynamic models of dimension up to 100 is indicative of the potential of the proposed filter in realizing the stated aim of successfully treating relatively larger dimensional filtering problems. (C) 2013 Elsevier Ltd. All rights reserved.

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We consider a Gaussian multiple access channel (GMAC) where the users are sensor nodes powered by energy harvesters. The energy harvesters may have finite or infinite buffer to store the harvested energy. First, we find the capacity region of a GMAC powered by transmit nodes with an infinite energy buffer. Next, we consider a GMAC with the transmitting nodes equipped with a finite energy buffer. Initially we assume perfect knowledge of the buffer state information at both the encoders and the decoder. We provide an achievable region for this case. We also generalize the achievable region when only partial information about buffer state is available at both the encoders and the decoder.

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In this paper, we study the achievable rate region of two-user Gaussian broadcast channel (GBC) when the messages to be transmitted to both the users take values from finite signal sets and the received signal is quantized at both the users. We refer to this channel as quantized broadcast channel (QBC). We first observe that the capacity region defined for a GBC does not carry over as such to QBC. Also, we show that the optimal decoding scheme for GBC (i.e., high SNR user doing successive decoding and low SNR user decoding its message alone) is not optimal for QBC. We then propose an achievable rate region for QBC based on two different schemes. We present achievable rate region results for the case of uniform quantization at the receivers. We find that rotation of one of the user's input alphabet with respect to the other user's alphabet marginally enlarges the achievable rate region of QBC when almost equal powers are allotted to both the users.

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Space-vector-based pulse width modulation (PWM) for a voltage source inverter (VSI) offers flexibility in terms of different switching sequences. Numerical simulation is helpful to assess the performance of a PWM method before actual implementation. A quick-simulation tool to simulate a variety of space-vector-based PWM strategies for a two-level VSI-fed squirrel cage induction motor drive is presented. The simulator is developed using C and Python programming languages, and has a graphical user interface (GUI) also. The prime focus being PWM strategies, the simulator developed is 40 times faster than MATLAB in terms of the actual time taken for a simulation. Simulation and experimental results are presented on a 5-hp ac motor drive.

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In this work, possibility of simulating biological organs in realtime using the Boundary Element Method (BEM) is investigated. Biological organs are assumed to follow linear elastostatic material behavior, and constant boundary element is the element type used. First, a Graphics Processing Unit (GPU) is used to speed up the BEM computations to achieve the realtime performance. Next, instead of the GPU, a computer cluster is used. Results indicate that BEM is fast enough to provide for realtime graphics if biological organs are assumed to follow linear elastostatic material behavior. Although the present work does not conduct any simulation using nonlinear material models, results from using the linear elastostatic material model imply that it would be difficult to obtain realtime performance if highly nonlinear material models that properly characterize biological organs are used. Although the use of BEM for the simulation of biological organs is not new, the results presented in the present study are not found elsewhere in the literature.

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The thermoacoustic prime mover (TAPM) has gained considerable attention as a pressure wave generator to drive pulse tube refrigerator (PTR) due to no moving parts, reasonable efficiency, use of environmental friendly working fluids etc. To drive PTCs, lower frequencies (f) with larger pressure amplitudes (Delta P) are essential, which are affected by geometric and operating parameters of TAPM as well as working fluids. For driving PTRs, a twin standing wave TAPM is built and studied by using different working fluids such as helium, argon, nitrogen and their binary mixtures. Simulation results of DeltaEc are compared with experimental data wherever possible. DeltaEc predicts slightly increased resonance frequencies, but gives larger Delta P and lower temperature difference Delta T across stack. High mass number working fluid leads to lower frequency with larger Delta P, but higher Delta T. Studies indicate that the binary gas mixture of right composition with lower Delta T can be arrived at to drive TAPM of given geometry. (C) 2013 Elsevier Ltd and IIR. All rights reserved.

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In the product conceptualization phase of design, sketches are often used for exploration of diverse behaviour patterns of the components to achieve the required functionality. This paper presents a method to animate the sketch produced using a tablet interface to aid verification of the desired behaviour. A sketch is a spatial organization of strokes whose perceptual organization helps one to visually interpret its components and their interconnections. A Gestalt based segmentation followed by interactive grouping and articulation, presented in this paper, enables one to use a mechanism simulation framework to animate the sketch in a “pick and drag” mode to visualize different configurations of the product and gain insight into the product’s behaviour.

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We discuss the computational bottlenecks in molecular dynamics (MD) and describe the challenges in parallelizing the computation-intensive tasks. We present a hybrid algorithm using MPI (Message Passing Interface) with OpenMP threads for parallelizing a generalized MD computation scheme for systems with short range interatomic interactions. The algorithm is discussed in the context of nano-indentation of Chromium films with carbon indenters using the Embedded Atom Method potential for Cr-Cr interaction and the Morse potential for Cr-C interactions. We study the performance of our algorithm for a range of MPI-thread combinations and find the performance to depend strongly on the computational task and load sharing in the multi-core processor. The algorithm scaled poorly with MPI and our hybrid schemes were observed to outperform the pure message passing scheme, despite utilizing the same number of processors or cores in the cluster. Speed-up achieved by our algorithm compared favorably with that achieved by standard MD packages. (C) 2013 Elsevier Inc. All rights reserved.

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This study presents the response of a vertically loaded pile in undrained clay considering spatially distributed undrained shear strength. The probabilistic study is performed considering undrained shear strength as random variable and the analysis is conducted using random field theory. The inherent soil variability is considered as source of variability and the field is modeled as two dimensional non-Gaussian homogeneous random field. Random field is simulated using Cholesky decomposition technique within the finite difference program and Monte Carlo simulation approach is considered for the probabilistic analysis. The influence of variance and spatial correlation of undrained shear strength on the ultimate capacity as summation of ultimate skin friction and end bearing resistance of pile are examined. It is observed that the coefficient of variation and spatial correlation distance are the most important parameters that affect the pile ultimate capacity.