摘要 :
Interference alignment is a key technique for communication scenarios with multiple interfering links. In several such scenarios, interference alignment was used to characterize the degrees of freedom of the channel. However, thes...
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Interference alignment is a key technique for communication scenarios with multiple interfering links. In several such scenarios, interference alignment was used to characterize the degrees of freedom of the channel. However, these degree-of-freedom capacity approximations are often too weak to make accurate predictions about the behavior of channel capacity at finite signal-to-noise ratios (${ssr SNR}{rm s}$). The aim of this paper is to significantly strengthen these results by showing that interference alignment can be used to characterize capacity to within a constant gap. We focus on real, time-invariant, frequency-flat X-channels. The only known solutions achieving the degrees of freedom of this channel are either based on real interference alignment or on layer-selection schemes. Neither of these solutions seems sufficient for a constant-gap capacity approximation. In this paper, we propose a new communication scheme and show that it achieves the capacity of the Gaussian X-channel to within a constant gap. To aid in this process, we develop a novel deterministic channel model. This deterministic model depends on the ${textstyle{{1}over{2}}}log ({ssr SNR})$ most-significant bits of the channel coefficients rather than only the single most-significant bit used in conventional deterministic models. The proposed deterministic model admits a wider range of achievable schemes that can be translated to the Gaussian channel. For this deterministic model, we find an approximately optimal communication scheme. We then translate this scheme for the deterministic channel to the original Gaussian X-channel and show that it achieves capacity to within a constant gap. This is the first constant-gap result for a general, fully-connected network requiring interference alignment.
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Noise is associated with all the components of the oscillator circuit; however, the major contribution of the noise in an oscillator is from the active device, which introduces amplitude modulation (AM) and phase modulation (PM) n...
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Noise is associated with all the components of the oscillator circuit; however, the major contribution of the noise in an oscillator is from the active device, which introduces amplitude modulation (AM) and phase modulation (PM) noise [1]-[103]. The conventional wisdom is to ignore AM component of the noise because the gain limiting effects of the active device operating under saturation, allowing only little variation in the output amplitude due to the noise in comparison to PM noise component, which directly affects the frequency stability of the oscillator and creates noise sidebands. But in reality, many oscillator topologies create significant AM noise, therefore effective noise contribution is the combination of 1/f spectrum with the 1/f 2 effect in all PM, makes the low_frequency noise much greater, and that's where the information in most modulated signals resides [1]-[3].
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Integrated navigation systems based on a tightly coupled integration scheme utilize pseudoranges and pseudorange rates from Global Positioning System (GPS) satellites measured by the receiver. The positioning accuracy is highly de...
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Integrated navigation systems based on a tightly coupled integration scheme utilize pseudoranges and pseudorange rates from Global Positioning System (GPS) satellites measured by the receiver. The positioning accuracy is highly dependent on the accuracy of the pseudoranges whose residual errors can deteriorate the overall positioning accuracy. The integrated system can be improved by the provision of more accurate pseudoranges through modeling the residual correlated errors. This paper utilizes parallel cascade identification (PCI), which is a nonlinear system identification technique, to model these correlated errors. To address the nonlinear error characteristics in the whole integrated navigation system, a nonlinear filter, i.e., mixture particle filter (M-PF), is employed to perform tightly coupled integration of a 3-D reduced inertial sensor system (RISS) with a GPS. The M-PF can accommodate the PCI models of the pseudorange errors in the measurement model. The results demonstrate the advantages of using M-PF-PCI for correcting the pseudoranges and enhancing the positioning solution as compared with M-PF-only, Kalman filter (KF)-PCI, and KF-only solutions.
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Accurate measurement of phase noise is one of the most difficult measurements in all of electrical engineering. The biggest challenge is the huge dynamic range required in most phase noise measurements. There are several methods t...
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Accurate measurement of phase noise is one of the most difficult measurements in all of electrical engineering. The biggest challenge is the huge dynamic range required in most phase noise measurements. There are several methods to measure phase noise, and the right one must be chosen to make the necessary measurements. To make a proper selection from the various methods, it is necessary to know and appreciate the weaknesses and strengths of each of the different techniques because none of these methods is perfect for every situation [1]?[44]. This article focuses on key phase noise measurement techniques for oscillators and reviews their advantages and disadvantages.
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Studies have shown that aortic calcification is associated with cardiovascular disease. In this study, a method for localization, centerline extraction, and segmentation of the thoracic aorta in noncontrast cardiac-computed tomogr...
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Studies have shown that aortic calcification is associated with cardiovascular disease. In this study, a method for localization, centerline extraction, and segmentation of the thoracic aorta in noncontrast cardiac-computed tomography (CT) images, toward the detection of aortic calcification, is presented. The localization of the right coronary artery ostium slice is formulated as a regression problem whose input variables are obtained from simple intensity features computed from a pyramid representation of the slice. The localization, centerline extraction, and segmentation of the aorta are formulated as optimal path detection problems. Dynamic programming is applied in the Hough space for localizing key center points in the aorta which guide the centerline tracing using a fast marching-based minimal path extraction framework. The input volume is then resampled into a stack of 2-D cross-sectional planes orthogonal to the obtained centerline. Dynamic programming is again applied for the segmentation of the aorta in each slice of the resampled volume. The obtained segmentation is finally mapped back to its original volume space. The performance of the proposed method was assessed on cardiac noncontrast CT scans and promising results were obtained.
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Endovascular image-guided interventions (EIGI) involve navigation of a catheter through the vasculature followed by application of treatment at the site of anomaly using live 2D projection images for guidance. 3D images acquired p...
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Endovascular image-guided interventions (EIGI) involve navigation of a catheter through the vasculature followed by application of treatment at the site of anomaly using live 2D projection images for guidance. 3D images acquired prior to EIGI are used to quantify the vascular anomaly and plan the intervention. If fused with the information of live 2D images they can also facilitate navigation and treatment. For this purpose 3D-2D image registration is required. Although several 3D-2D registration methods for EIGI achieve registration accuracy below 1 mm, their clinical application is still limited by insufficient robustness or reliability. In this paper, we propose a 3D-2D registration method based on matching a 3D vasculature model to intensity gradients of live 2D images. To objectively validate 3D-2D registration methods, we acquired a clinical image database of 10 patients undergoing cerebral EIGI and established “gold standard” registrations by aligning fiducial markers in 3D and 2D images. The proposed method had mean registration accuracy below 0.65 mm, which was comparable to tested state-of-the-art methods, and execution time below 1 s. With the highest rate of successful registrations and the highest capture range the proposed method was the most robust and thus a good candidate for application in EIGI.
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With the rapidly evolving technology of the smart grid and electric vehicles (EVs), the battery has emerged as the most prominent energy storage device, attracting a significant amount of attention. The very recent discussions abo...
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With the rapidly evolving technology of the smart grid and electric vehicles (EVs), the battery has emerged as the most prominent energy storage device, attracting a significant amount of attention. The very recent discussions about the performance of lithium-ion (Li-ion) batteries in the Boeing 787 have confirmed so far that, while battery technology is growing very quickly, developing cells with higher power and energy densities, it is equally important to improve the performance of the battery management system (BMS) to make the battery a safe, reliable, and cost-efficient solution. The specific characteristics and needs of the smart grid and EVs, such as deep charge/discharge protection and accurate state-of-charge (SOC) and state-of-health (SOH) estimation, intensify the need for a more efficient BMS. The BMS should contain accurate algorithms to measure and estimate the functional status of the battery and, at the same time, be equipped with state-of-the-art mechanisms to protect the battery from hazardous and inefficient operating conditions.
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We describe BonnPlaceLegal, an algorithm for VLSI placement legalization. Based on a minimum-cost flow algorithm that iteratively augments flows along paths, our approach ensures that only augmentations are considered that can be ...
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We describe BonnPlaceLegal, an algorithm for VLSI placement legalization. Based on a minimum-cost flow algorithm that iteratively augments flows along paths, our approach ensures that only augmentations are considered that can be realized exactly by cell movements. Hence, this method avoids realization problems that are inherent to previous flow-based legalization algorithms. As a result, it combines the global perspective of minimum-cost flow approaches with the efficiency of local search algorithms. The tool is mainly designed to minimize total and maximum cell movement, but it is flexible enough to optimize other objective functions provided that the effect of single cell movements on them can be estimated efficiently. We compare our approach to legalization tools from industry and academia by experiments on dense recent real-world designs and public benchmarks. The results show that we are much faster and produce significantly better results in terms of average (linear and quadratic) and maximum movement than any other tool. The experiments also demonstrate that by minimizing squared movement we also produce a smaller increase in net length than the other tools.
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Lane detection is important in many advanced driver-assistance systems (ADAS). Vision-based lane detection algorithms are widely used and generally use gradient information as a lane feature. However, gradient values between lanes...
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Lane detection is important in many advanced driver-assistance systems (ADAS). Vision-based lane detection algorithms are widely used and generally use gradient information as a lane feature. However, gradient values between lanes and roads vary with illumination change, which degrades the performance of lane detection systems. In this paper, we propose a gradient-enhancing conversion method for illumination-robust lane detection. Our proposed gradient-enhancing conversion method produces a new gray-level image from an RGB color image based on linear discriminant analysis. The converted images have large gradients at lane boundaries. To deal with illumination changes, the gray-level conversion vector is dynamically updated. In addition, we propose a novel lane detection algorithm, which uses the proposed conversion method, adaptive Canny edge detector, Hough transform, and curve model fitting method. We performed several experiments in various illumination environments and confirmed that the gradient is maximized at lane boundaries on the road. The detection rate of the proposed lane detection algorithm averages 96% and is greater than 93% in very poor environments.
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The current-source power of an implanted stimulator is reduced almost to the theoretical minimum by driving the electrodes directly from the secondary port of the inductive link with a dedicated zero-voltage switching power supply...
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The current-source power of an implanted stimulator is reduced almost to the theoretical minimum by driving the electrodes directly from the secondary port of the inductive link with a dedicated zero-voltage switching power supply. A feedback loop confined to the secondary of the inductive link adjusts the timing and conduction angle of switching to provide just the right amount of supply voltage needed for keeping the current-source voltage constant at or slightly above the compliance limit. Since drive is based on current rather than voltage, and supply-voltage update is near real-time, the quality of the current pulses is high regardless of how the electrode impedance evolves during stimulation. By scaling the switching frequency according to power demand, the technique further improves overall power consumption of the stimulator. The technique is implemented with a very simple control circuitry comprising a comparator, a Schmitt trigger and a logic gate of seven devices in addition to an on-chip switch and an off-chip capacitor. The power consumed by the proposed supply circuit itself is no larger than what the linear regulator of a conventional supply typically consumes for the same stimulation current. Still, the sum of supply and current-source power is typically between 20% and 75% of the conventional source power alone. Functionality of the proposed driver is verified experimentally on a proof-of-concept prototype built with 3.3 V devices in a 0.18 $mu {rm m}$ CMOS technology.
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