780 research outputs found

    Measurements of Surface Diffusivity and Coarsening During Pulsed Laser Deposition

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    Pulsed Laser Deposition (PLD) of homoepitaxial SrTiO3 was studied with in-situ x-ray specular reflectivity and surface diffuse x-ray scattering. Unlike prior reflectivity-based studies, these measurements access both the time- and the length-scales of the evolution of the surface morphology during growth. In particular, we show that this technique allows direct measurements of the diffusivity for both inter- and intra-layer transport. Our results explicitly limit the possible role of island break-up, demonstrate the key roles played by nucleation and coarsening in PLD, and place an upper bound on the Ehrlich-Schwoebel (ES) barrier for downhill diffusion

    Extraction of primary and secondary frequency control from active power generation data of power plants

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    Frequency control is a vital component of a secure and robust power grid and it ought to be closely monitored. Frequency control consists of two main components; primary and secondary control and their contributions are usually aggregated in the active power generation data of a plant, which is acquired via Supervisory Control And Data Acquisition. In many cases, such as in Turkey, they are demanded to be evaluated separately due to different impacts on power system or different financial policies. However, this is not usually a straightforward process since primary and secondary response cannot be obtained distinctly. In this work, Extraction of Primary and Secondary Control (EPSCon) algorithm is introduced to extract primary and secondary response over active power generation data. Based on time and frequency domain characteristics of primary and secondary response, EPSCon is developed on a Expectation-Maximization type recursive scheme employing Generalized Cross Correlation and ℓ1 Trend Filtering techniques. Favorably, EPSCon uses a simple plant model built upon basic governor and plant load controller technical characteristics as an initial estimate of primary and secondary response. © 2015 Elsevier Ltd. All rights reserved

    Challenges and some new directions in channel coding

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    Three areas of ongoing research in channel coding are surveyed, and recent developments are presented in each area: Spatially coupled low-density parity-check (LDPC) codes, nonbinary LDPC codes, and polar coding. © 2015 KICS

    An empirical eigenvalue-threshold test for sparsity level estimation from compressed measurements

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    Compressed sensing allows for a significant reduction of the number of measurements when the signal of interest is of a sparse nature. Most computationally efficient algorithms for signal recovery rely on some knowledge of the sparsity level, i.e., the number of non-zero elements. However, the sparsity level is often not known a priori and can even vary with time. In this contribution we show that it is possible to estimate the sparsity level directly in the compressed domain, provided that multiple independent observations are available. In fact, one can use classical model order selection algorithms for this purpose. Nevertheless, due to the influence of the measurement process they may not perform satisfactorily in the compressed sensing setup. To overcome this drawback, we propose an approach which exploits the empirical distributions of the noise eigenvalues. We demonstrate its superior performance compared to state-of-the-art model order estimation algorithms numerically. © 2014 EURASIP

    Robust Transmission of Multi-View Video Streams Using Flexible Macroblock Ordering and Systematic LT codes

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    The transmission of fully compatible H.264/AVC multi-view video coded streams over packet erasure networks is examined. Macroblock classification into unequally important slice groups is considered using the flexible macroblock ordering (FMO) tool of H.264/AVC. Systematic LT codes are used for error protection due to their low complexity and advanced performance. The optimal slice grouping and channel rate allocation are jointly determined by an iterative optimization algorithm based on dynamic programming. The experimental evaluation clearly demonstrates the validity of the proposed method

    An efficient parallelization technique for high throughput FFT-ASIPs

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    Fast Fourier Transformation (FFT) and it's inverse (IFFT) are used in Orthogonal Frequency Division Multiplexing (OFDM) systems for data (de)modulation. The transformations are the kernel tasks in an OFDM implementation, and are the most processing-intensive ones. Recent trends in the electronic consumer market require OFDM implementations to be flexible, making a trade-off between area, energy-efficiency, flexibility and timing a necessity. This has spurred the development of Application-Specific Instruction-Set Processors (ASIPs) for FFT processing. Parallelization is an architectural parameter that significantly influence design goals. This paper presents an analysis of the efficiency of parallelization techniques for an FFT-ASIP. It is shown that existing techniques are inefficient for high throughput applications such as Ultra Wideband (UWB), because of memory bottlenecks. Therefore, an interleaved execution technique which exploits temporal parallelism is proposed. With this technique, it is possible to meet the throughput requirement of UWB (409.6 Msamples/s) with only 4 non-trivial butterfly units for an ASIP that runs at 400MHz. © 2006 IEEE

    Sparsity order estimation for single snapshot compressed sensing

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    In this paper we discuss the estimation of the spar-sity order for a Compressed Sensing scenario where only a single snapshot is available. We demonstrate that a specific design of the sensing matrix based on Khatri-Rao products enables us to transform this problem into the estimation of a matrix rank in the presence of additive noise. Thereby, we can apply existing model order selection algorithms to determine the sparsity order. The matrix is a rearranged version of the observation vector which can be constructed by concatenating a series of non-overlapping or overlapping blocks of the original observation vector. In both cases, a Khatri-Rao structured measurement matrix is required with the main difference that in the latter case, one of the factors must be a Vandermonde matrix. We discuss the choice of the parameters and show that an increasing amount of block overlap improves the sparsity order estimation but it increases the coherence of the sensing matrix. We also explain briefly that the proposed measurement matrix design introduces certain multilinear structures into the observations which enables us to apply tensor-based signal processing, e.g., for enhanced denoising or improved sparsity order estimation. © 2014 IEEE

    Space weather studies of IONOLAB group

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    IONOLAB is an interdisciplinary research group dedicated for handling the challenges of near earth environment on communication, positioning and remote sensing systems. IONOLAB group contributes to the space weather studies by developing state-of-the-art analysis and imaging techniques. On the website of IONOLAB group, www.ionolab.org, four unique space weather services, namely, IONOLAB-TEC, IRI-PLAS-2015, IRI-PLAS-MAP and IRI-PLAS-STEC, are provided in a user friendly graphical interface unit. Newly developed algorithm for ionospheric tomography, IONOLAB-CIT, provides not only 3-D electron density but also tracking of ionospheric state with high reliability and fidelity. The algorithm for ray tracing through ionosphere, IONOLAB-RAY, provides a simulation environment in all communication bands. The background ionosphere is generated in voxels where IRI-Plas electron density is used to obtain refractive index. One unique feature is the possible update of ionospheric state by insertion of Total Electron Content (TEC) values into IRI-Plas. Both ordinary and extraordinary paths can be traced with high ray and low ray scenarios for any desired date, time and transmitter location. 2-D regional interpolation and mapping algorithm, IONOLAB-MAP, is another tool of IONOLAB group where automatic TEC maps with Kriging algorithm are generated from GPS network with high spatio-temporal resolution. IONOLAB group continues its studies in all aspects of ionospheric and plasmaspheric signal propagation, imaging and mapping. © 2016 IEEE
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