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  • Articles  (721)
  • Institute of Electrical and Electronics Engineers (IEEE)  (721)
  • American Chemical Society (ACS)
  • American Geophysical Union
  • National Academy of Sciences
  • Springer
  • 2015-2019  (721)
  • 2005-2009
  • 1990-1994
  • 1980-1984
  • 2017  (721)
  • IEEE Transactions on Signal Processing  (404)
  • IEEE Transactions on Nuclear Science  (317)
  • 1419
  • 1428
  • Electrical Engineering, Measurement and Control Technology  (404)
  • Physics  (317)
Collection
  • Articles  (721)
Source
Publisher
  • Institute of Electrical and Electronics Engineers (IEEE)  (721)
  • American Chemical Society (ACS)
  • American Geophysical Union
  • National Academy of Sciences
  • Springer
Years
  • 2015-2019  (721)
  • 2005-2009
  • 1990-1994
  • 1980-1984
Year
Journal
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  • 1
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    Stabilization of Particle Discrimination Efficiencies for Neutron Spectrum Unfolding With Organic Scintillators (2017)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2017-03-21
    Description: The literature discussing pulse-shape discrimination (PSD) in organic scintillators dates back several decades. However, little has been written about PSD techniques that are optimized for neutron spectrum unfolding. Variation in $n$ - $gamma $ misclassification rates and in $gamma /n$ ratio of incident fields can distort the neutron pulse-height response of scintillators and these distortions can in turn cause large errors in unfolded spectra. New applications in arms-control verification call for detection of lower-energy neutrons, for which PSD is particularly problematic. In this article, we propose techniques for removing distortions on pulse-height response that result from the merging of PSD distributions in the low-pulse-height region. These techniques take advantage of the repeatable shapes of PSD distributions that are governed by the counting statistics of scintillation-photon populations. We validate the proposed techniques using accelerator-based time-of-flight measurements and then demonstrate them by unfolding the Watt spectrum from measurement with a 252 Cf neutron source.
    Print ISSN: 0018-9499
    Electronic ISSN: 1558-1578
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Physics
    Published by Institute of Electrical and Electronics Engineers (IEEE)
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  • 2
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    Position Error Correction Using Homography in Discretized Positioning Circuit for Gamma-Ray Imaging Detection System (2017)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2017-03-21
    Description: A discretized positioning circuit (DPC) based on a resistive network has been developed to reduce the size of a gamma-ray detection system using multi-anode photomultiplier tubes (MA-PMT) in an array, because it can drastically decrease the number of output channels. The output signal from the gamma-ray detection system is a current pulse generated in each tube that contains information about the gamma-ray energy and detecting position in the array. The output current pulse is distributed to four outputs according to the resistance ratio of the resistive network in the DPC, and the detected position is estimated using the height values of the four distributed current pulses. However, owing to parasitic capacitors of MA-PMT connected in parallel to resistors in the resistive network, the four output pulses are affected by the RC time constants. In particular, when the duration of the input signal is not long enough, the height values of the distributed pulses are reduced, and thereby the position error increases significantly. In this paper, we present a new distortion correction method that considers the pulse duration and the RC time constant. In order to correct the position error, we employed homography, which is a coordinate transformation method. The ideal grid was mapped to a new grid for the distorted position. Using this method, error correction was completely achieved, even for short current pulses.
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Physics
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  • 3
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    Solution-Grown Rubrene Crystals as Radiation Detecting Devices (2017)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2017-03-21
    Description: There has been increased interest in organic semiconductors over the last decade because of their unique properties. Of these, 5, 6, 11, 12-tetraphenylnaphthacene (rubrene) has generated the most interest because of its high charge carrier mobility. In this work, large single crystals with a volume of ~1 cm 3 were grown from solution by a temperature reduction technique. The faceted crystals had flat surfaces and cm-scale, visually defect-free areas suitable for physical characterization. X-ray diffraction analysis indicates that solvent does not incorporate into the crystals and photoluminescence spectra are consistent with pristine, high-crystallinity rubrene. Furthermore, the response curve to pulsed optical illumination indicates that the solution grown crystals are of similar quality to those grown by physical vapor transport, albeit larger. The good quality of these crystals in combination with the improvement of electrical contacts by application of conductive polymer on the graphite electrodes have led to the clear observation of alpha particles with these rubrene detectors. Preliminary results with a 252 Cf source generate a small signal with the rubrene detector and may demonstrate that rubrene can also be used for detecting high-energy neutrons.
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Physics
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  • 4
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    A Novel Read-Out Electronics Design Based on 1-Bit Sigma-Delta Modulation (2017)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2017-03-21
    Description: The conventional front-end electronics for PET imaging consist of an energy circuit and a timing circuit. A single channel in front-end electronics typically requires several amplifiers, an ADC and a TDC. In this paper, we present a novel front-end electronic design using 1-bit sigma-delta ( $boldsymbol {Sigma }$ - $boldsymbol {Delta }$ ) modulation and an FPGA. The new design requires only one analog amplifier per channel. The output of the analog amplifier is read directly by the FPGA. Both the energy and timing calculation are implemented in FPGA firmware. The scope of this paper is to introduce the novel design in detail and to evaluate its performance in energy and dark current measurements. Simulink simulations were performed to validate the design with ideal components. A one-channel prototype circuit was built to assess the design with real components. The prototype circuit was tested with different input signals, including test pulses, pulse signals from a PMT detector, DC current signals and dark current signals from an SiPM sensor. Both the simulation and experimental results show that the method is inherently stable and has excellent accuracy and linearity in energy and dark current measurements. The prototype analog board was built with discrete components cost about $ 0.5 in total. The power consumption was about 20 mW. We conclude that the new method provides a cost-efficient and power-efficient way to accurately measure the energies of analog pulses and dark currents from detectors. The timing performance of this method is currently under evaluation.
    Print ISSN: 0018-9499
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Physics
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  • 5
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    Laplacian Eigenmaps From Sparse, Noisy Similarity Measurements (2017)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2017-02-11
    Description: Manifold learning and dimensionality reduction techniques are ubiquitous in science and engineering, but can be computationally expensive procedures when applied to large datasets or when similarities are expensive to compute. To date, little work has been done to investigate the tradeoff between computational resources and the quality of learned representations. We present both theoretical and experimental explorations of this question. In particular, we consider Laplacian eigenmaps embeddings based on a kernel matrix, and explore how the embeddings behave when this kernel matrix is corrupted by occlusion and noise. Our main theoretical result shows that under modest noise and occlusion assumptions, we can (with high probability) recover a good approximation to the Laplacian eigenmaps embedding based on the uncorrupted kernel matrix. Our results also show how regularization can aid this approximation. Experimentally, we explore the effects of noise and occlusion on Laplacian eigenmaps embeddings of two real-world datasets, one from speech processing and one from neuroscience, as well as a synthetic dataset.
    Print ISSN: 1053-587X
    Electronic ISSN: 1941-0476
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Signal Processing Society.
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  • 6
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    High Dimensional Low Rank Plus Sparse Matrix Decomposition (2017)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2017-02-11
    Description: This paper is concerned with the problem of low-rank plus sparse matrix decomposition for big data. Conventional algorithms for matrix decomposition use the entire data to extract the low-rank and sparse components, and are based on optimization problems with complexity that scales with the dimension of the data, which limits their scalability. Furthermore, existing randomized approaches mostly rely on uniform random sampling, which is quite inefficient for many real world data matrices that exhibit additional structures (e.g., clustering). In this paper, a scalable subspace-pursuit approach that transforms the decomposition problem to a subspace learning problem is proposed. The decomposition is carried out by using a small data sketch formed from sampled columns/rows. Even when the data are sampled uniformly at random, it is shown that the sufficient number of sampled columns/rows is roughly $mathcal {O}(r mu)$ , where $mu$ is the coherency parameter and $r$ is the rank of the low-rank component. In addition, adaptive sampling algorithms are proposed to address the problem of columns/rows sampling from structured data. We provide an analysis of the proposed method with adaptive sampling and show that adaptive sampling makes the required number of sampled columns/rows invariant to the distribution of the data. The proposed approach is amenable to online implementation and an online scheme is proposed.
    Print ISSN: 1053-587X
    Electronic ISSN: 1941-0476
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Signal Processing Society.
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  • 7
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    An Exact and Fast Computation of Discrete Fourier Transform for Polar and Spherical Grid (2017)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2017-02-11
    Description: Numerous applied problems of two-dimensional (2-D) and 3-D imaging are formulated in continuous domain. They place great emphasis on obtaining and manipulating the Fourier transform in polar and spherical coordinates. However, the translation of continuum ideas with the discrete sampled data on a Cartesian grid is problematic. There exists no exact and fast solution to the problem of obtaining discrete Fourier transform for polar and spherical grids in the literature. In this paper, we develop exact algorithms to the above problem for 2-D and 3-D, which involve only 1-D equispaced fast Fourier transform with no interpolation or approximation at any stage. The result of the proposed approach leads to a fast solution with very high accuracy. We describe the computational procedure to obtain the solution in both 2-D and 3-D, which includes fast forward and inverse transforms. We find the nested multilevel matrix structure of the inverse process, and we propose a hybrid grid and use a preconditioned conjugate gradient method that exhibits a drastic improvement in the condition number.
    Print ISSN: 1053-587X
    Electronic ISSN: 1941-0476
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Signal Processing Society.
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  • 8
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    Recovery of Sparse Signals Using Multiple Orthogonal Least Squares (2017)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2017-02-11
    Description: Sparse recovery aims to reconstruct sparse signals from compressed linear measurements. In this paper, we propose a sparse recovery algorithm called multiple orthogonal least squares (MOLS), which extends the well-known orthogonal least squares (OLS) algorithm by allowing multiple $L$ indices to be selected per iteration. Owing to its ability to catch multiple support indices in each selection, MOLS often converges in fewer iterations and hence improves the computational efficiency over the conventional OLS algorithm. Theoretical analysis shows that MOLS ( $L > 1$ ) performs exact recovery of $K$ -sparse signals ( $K > 1$ ) in at most $K$ iterations, provided that the sensing matrix obeys the restricted isometry property with isometry constant $delta _{LK} 〈 {sqrt{L}}/({sqrt{K} + 2 sqrt{L}}).$ When $L = 1,$ MOLS reduces to the conventional OLS algorithm and our analysis shows that exact recovery is guaranteed under $delta_{K +1} 〈 1 / (sqrt{K} + 2)$ . This condition is nearly optimal with respect to $delta _{K+1}$ in the sense that, even with a small relaxation (e.g., $delta_{K + 1} = 1 / sqrt{K}$ ), exact recovery with OLS may not be guaranteed. The recovery performance of MOLS in the noisy sce- ario is also studied. It is shown that stable recovery of sparse signals can be achieved with the MOLS algorithm when the signal-to-noise ratio scales linearly with the sparsity level of input signals.
    Print ISSN: 1053-587X
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    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Signal Processing Society.
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  • 9
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    Signal Processing on Graphs: Causal Modeling of Un structured Data (2017)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2017-02-11
    Description: Many applications collect a large number of time series, for example, the financial data of companies quoted in a stock exchange, the health care data of all patients that visit the emergency room of a hospital, or the temperature sequences continuously measured by weather stations across the US. These data are often referred to as un structured. The first task in its analytics is to derive a low dimensional representation, a graph or discrete manifold, that describes well the inter relations among the time series and their intra relations across time. This paper presents a computationally tractable algorithm for estimating this graph that structures the data. The resulting graph is directed and weighted, possibly capturing causal relations, not just reciprocal correlations as in many existing approaches in the literature. A convergence analysis is carried out. The algorithm is demonstrated on random graph datasets and real network time series datasets, and its performance is compared to that of related methods. The adjacency matrices estimated with the new method are close to the true graph in the simulated data and consistent with prior physical knowledge in the real dataset tested.
    Print ISSN: 1053-587X
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    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Signal Processing Society.
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  • 10
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    On Demodulation, Ridge Detection, and Synchrosqueezing for Multicomponent Signals (2017)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2017-02-11
    Description: In this paper, we present a novel technique for the retrieval of the modes of a multicomponent signal using a time-frequency (TF) representation of the signal. Our approach is based on a novel ridge extraction method that takes into account the fact that the TF representation is both discrete in time and frequency, followed by a demodulation procedure. Numerical results show the benefits of the proposed approach for mode reconstruction in comparison to similar techniques that do not make use of demodulation. Furthermore, numerical investigations show that the proposed approach sharpens the TF representation on which it is built.
    Print ISSN: 1053-587X
    Electronic ISSN: 1941-0476
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Signal Processing Society.
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