78 research outputs found

    Neural Network-Based DOA Estimation in the Presence of Non-Gaussian Interference

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    This work addresses the problem of direction-of-arrival (DOA) estimation in the presence of non-Gaussian, heavy-tailed, and spatially-colored interference. Conventionally, the interference is considered to be Gaussian-distributed and spatially white. However, in practice, this assumption is not guaranteed, which results in degraded DOA estimation performance. Maximum likelihood DOA estimation in the presence of non-Gaussian and spatially colored interference is computationally complex and not practical. Therefore, this work proposes a neural network (NN) based DOA estimation approach for spatial spectrum estimation in multi-source scenarios with a-priori unknown number of sources in the presence of non-Gaussian spatially-colored interference. The proposed approach utilizes a single NN instance for simultaneous source enumeration and DOA estimation. It is shown via simulations that the proposed approach significantly outperforms conventional and NN-based approaches in terms of probability of resolution, estimation accuracy, and source enumeration accuracy in conditions of low SIR, small sample support, and when the angular separation between the source DOAs and the spatially-colored interference is small.Comment: Submitted to IEEE Transactions on Aerospace and Electronic System

    Neural Network-Based Multi-Target Detection within Correlated Heavy-Tailed Clutter

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    This work addresses the problem of range-Doppler multiple target detection in a radar system in the presence of slow-time correlated and heavy-tailed distributed clutter. Conventional target detection algorithms assume Gaussian-distributed clutter, but their performance is significantly degraded in the presence of correlated heavy-tailed distributed clutter. Derivation of optimal detection algorithms with heavy-tailed distributed clutter is analytically intractable. Furthermore, the clutter distribution is frequently unknown. This work proposes a deep learning-based approach for multiple target detection in the range-Doppler domain. The proposed approach is based on a unified NN model to process the time-domain radar signal for a variety of signal-to-clutter-plus-noise ratios (SCNRs) and clutter distributions, simplifying the detector architecture and the neural network training procedure. The performance of the proposed approach is evaluated in various experiments using recorded radar echoes, and via simulations, it is shown that the proposed method outperforms the conventional cell-averaging constant false-alarm rate (CA-CFAR), the ordered-statistic CFAR (OS-CFAR), and the adaptive normalized matched-filter (ANMF) detectors in terms of probability of detection in the majority of tested SCNRs and clutter scenarios.Comment: Accepted to IEEE Transactions on Aerospace and Electronic System

    Elevated Uptake of Plasma Macromolecules by Regions of Arterial Wall Predisposed to Plaque Instability in a Mouse Model

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    Atherosclerosis may be triggered by an elevated net transport of lipid-carrying macromolecules from plasma into the arterial wall. We hypothesised that whether lesions are of the thin-cap fibroatheroma (TCFA) type or are less fatty and more fibrous depends on the degree of elevation of transport, with greater uptake leading to the former. We further hypothesised that the degree of elevation can depend on haemodynamic wall shear stress characteristics and nitric oxide synthesis. Placing a tapered cuff around the carotid artery of apolipoprotein E -/- mice modifies patterns of shear stress and eNOS expression, and triggers lesion development at the upstream and downstream cuff margins; upstream but not downstream lesions resemble the TCFA. We measured wall uptake of a macromolecular tracer in the carotid artery of C57bl/6 mice after cuff placement. Uptake was elevated in the regions that develop lesions in hyperlipidaemic mice and was significantly more elevated where plaques of the TCFA type develop. Computational simulations and effects of reversing the cuff orientation indicated a role for solid as well as fluid mechanical stresses. Inhibiting NO synthesis abolished the difference in uptake between the upstream and downstream sites. The data support the hypothesis that excessively elevated wall uptake of plasma macromolecules initiates the development of the TCFA, suggest that such uptake can result from solid and fluid mechanical stresses, and are consistent with a role for NO synthesis. Modification of wall transport properties might form the basis of novel methods for reducing plaque rupture

    Saliency maps for finding changes in visual scenes?

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    Sudden changes in the environment reliably summon attention. This rapid change detection appears to operate in a similar fashion as pop-out in visual search, the phenomenon that very salient stimuli are directly attended, independently of the number of distracting objects. Pop-out is usually explained by the workings of saliency maps, i.e., map-like representations that code for the conspicuity at each location of the visual field. While past research emphasized similarities between pop-out search and change detection, our study highlights differences between the saliency computations in the two tasks: in contrast to pop-out search, saliency computation in change detection (i) operates independently across different stimulus properties (e.g., color and orientation), and (ii) is little influenced by trial history. These deviations from pop-out search are not due to idiosyncrasies of the stimuli or task design, as evidenced by a replication of standard findings in a comparable visual-search design. To explain these results, we outline a model of change detection involving the computation of feature-difference maps, which explains the known similarities and differences with visual search

    It Pays to Modify Existing Crude Preheat Trains to Conserve More Energy!

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    With the cost of fuel now being so high, maximum recovery of available waste heat to preheat crude oil is an essential step in reducing the fuel consumption in a refinery. Foster Wheeler Energy Corporation has developed a special computer program called EXTRA (EXchanger TRAin) which can be used to determine which modifications to an existing crude preheat train will be most effective in economically recovering additional waste heat. The program can rigorously develop temperature profiles and heat exchanger duties in any existing, new or modified crude preheat train. Rating of existing exchangers, design of new exchangers and total capital and utility costs for new equipment is also provided. The program allows the user to specify any type of configuration that he may want to explore. The resulting cost and other information developed by the program can then be used to find the exchanger train network which will provide the maximum crude preheat for any specified economic criterion on new capital investment. A detailed case study is shown in which EXTRA is used to modify an existing crude preheat train

    On an interpolation problem of Dym and Gohberg

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