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Uncertainty Quantification with Invertible Neural Networks for Signal Integrity Applications

Uncertainty Quantification with Invertible Neural Networks f...

International Conference on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO)

作者： Osama Waqar Bhatti Oluwaseyi Akinwande Madhavan Swaminathan School of Electrical and Computer Engineering School of Material Science and Engineering 3D Systems Packaging Research Center (PRC) Georgia Institute of Technology Atlanta GA Georgia

ISBN: (纸本)9781665486347

We present a machine learning based tool to quantify uncertainty for prediction problems regarding signal integrity. Harnessing invertible neural networks, we convert the inverse posterior distribution given by the network to address uncertainty in frequency responses as a function of design space parameters. As an example, we consider a differential plated-through-hole via in package core and predict S-parameters from its geometrical properties. Results show 3.3 % normalized mean squared error when compared with responses from a fullwave EM simulator.

关键词： Solid modeling Uncertainty Three-dimensional displays Simulation Neural networks Predictive models Scattering parameters

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Data-Adaptive Symmetric CUSUM for Sequential Change Detection

arXiv

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arXiv 2022年

作者： Ahad, Nauman Davenport, Mark A. Xie, Yao The School of Electrical and Computer Engineering Georgia Tech AtlantaGA30302 United States The School of Industrial and Systems Engineering Georgia Tech AtlantaGA30302 United States

Detecting change points sequentially in a streaming setting, especially when both the mean and the variance of the signal can change, is often a challenging task. A key difficulty in this context often involves setting an appropriate detection threshold, which for many standard change statistics may need to be tuned depending on the pre-change and post-change distributions. This presents a challenge in a sequential change detection setting when a signal switches between multiple distributions. For example, consider a signal where change points are indicated by increases/decreases in the mean and variance of the signal. In this context, we would like to be able to compare our change statistic to a fixed threshold that will be symmetric to either increases or decreases in the mean and variance. Unfortunately, change point detection schemes that use the log-likelihood ratio, such as CUSUM and GLR, are quick to react to changes but are not symmetric when both the mean and the variance of the signal change. This makes it difficult to set a single threshold to detect multiple change points sequentially in a streaming setting. We propose a modified version of CUSUM that we call Data-Adaptive Symmetric CUSUM (DAS-CUSUM). The DAS-CUSUM change point detection procedure is symmetric for changes between distributions, making it suitable to set a single threshold to detect multiple change points sequentially in a streaming setting. We provide results that relate to the expected detection delay and average run length for our proposed procedure. Extensive simulations are used to validate these results. Experiments on real-world data further show the utility of using DAS-CUSUM over both CUSUM and GLR. © 2022, CC BY.

关键词： Change detection

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RSRP Measurement Based Channel Autocorrelation Estimation for IRS-Aided Wideband Communication

RSRP Measurement Based Channel Autocorrelation Estimation fo...

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IEEE Conference on Wireless Communications and Networking

作者： He Sun Lipeng Zhu Weidong Mei Rui Zhang Department of Electrical and Computer Engineering National University of Singapore Singapore National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China China School of Science and Engineering Shenzhen Research Institute of Big Data Chinese University of Hong Kong Shenzhen Guangdong China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

The passive and frequency-flat reflection of IRS, as well as the high-dimensional IRS-reflected channels, have posed significant challenges for efficient IRS channel estimation, especially in wideband communication systems with significant multi-path channel delay spread. To address these challenges, we propose a novel neural network (NN)-empowered framework for IRS channel autocorrelation matrix estimation in wideband orthogonal frequency division multiplexing (OFDM) systems. This framework relies only on the easily accessible reference signal received power (RSRP) measurements at users in existing wideband communication systems, without requiring additional pilot transmission. Based on the estimates of channel autocorrelation matrix, the passive reflection of IRS is optimized to maximize the average user received signal-to-noise ratio (SNR) over all subcarriers in the OFDM system. Numerical results verify that the proposed algorithm significantly outperforms existing power-measurement-based IRS reflection designs in wideband channels.

关键词： Power measurement Upper bound OFDM Simulation Channel estimation Estimation Reflection Autocorrelation Wideband Signal to noise ratio

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Learning of Nash Equilibria in Risk-Averse Games

arXiv

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arXiv 2024年

作者： Wang, Zifan Shen, Yi Zavlanos, Michael M. Johansson, Karl H. Division of Decision and Control Systems School of Electrical Enginnering and Computer Science KTH Royal Institute of Technology Digital Futures StockholmSE-10044 Sweden The Department of Mechanical Engineering and Materials Science Duke University DurhamNC United States

This paper considers risk-averse learning in convex games involving multiple agents that aim to minimize their individual risk of incurring significantly high costs. Specifically, the agents adopt the conditional value at risk (CVaR) as a risk measure with possibly different risk levels. To solve this problem, we propose a first-order risk-averse leaning algorithm, in which the CVaR gradient estimate depends on an estimate of the Value at Risk (VaR) value combined with the gradient of the stochastic cost function. Although estimation of the CVaR gradients using finitely many samples is generally biased, we show that the accumulated error of the CVaR gradient estimates is bounded with high probability. Moreover, assuming that the risk-averse game is strongly monotone, we show that the proposed algorithm converges to the risk-averse Nash equilibrium. We present numerical experiments on a Cournot game example to illustrate the performance of the proposed method. Copyright © 2024, The Authors. All rights reserved.

关键词： Risk assessment

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Strong Coupling Induced Ultrasensitive Chiral Detection by Metal-Dielectric Hybrid Metasurface

SSRN

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SSRN 2024年

作者： Jia, Tianxu Li, Bingjue Gu, Bing Zhan, Qiwen Rui, Guanghao Department of Optical Engineering School of Electronic Science and Engineering Southeast University Jiangsu Nanjing211189 China School of Mechanical Engineering Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments Southeast University Nanjing211189 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Zhangjiang Laboratory 100 Haike Road Shanghai201204 China

Circular dichroism (CD) spectroscopy struggles to detect weak signals from small, chiral molecules due to limitations in light absorption. This study introduces a method for significantly enhancing CD signals using a metal-dielectric hybrid metasurface. The metasurface creates a superchiral hotspot that amplifies the chirality of nearby molecules. Two techniques are proposed to overcome signal cancellation between the intrinsic and induced signals to achieve an overall enhancement of the CD signal by up to 23,630 times. This approach has the potential for ultrasensitive detection of chiral molecules at the nanoscale, with applications in pharmacology, toxicology, and life sciences. © 2024, The Authors. All rights reserved.

关键词： Dichroism

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Topological Flat Bands in Self-Complementary Plasmonic Metasurfaces

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Physical Review Letters 2022年第25期129卷 253001-253001页

作者： Zhixia Xu Xianghong Kong Jie Chang Daniel F. Sievenpiper Tie Jun Cui State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China School of Information Science and Technology Dalian Maritime University Dalian 116026 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore Electrical and Computer Engineering Department University of California San Diego San Diego California 92093 USA

Photonics can be confined in real space with dispersion vanishing in the momentum space due to destructive interference. In this Letter, we report the experimental realization of flat bands with nontrivial topology in a self-complementary plasmonic metasurface. The band diagram and compact localized states are measured. In these nontrivial band gaps, we observe the topological edge states by near-field measurements. Furthermore, we propose a digitalized metasurface by loading controllable diodes with C3 symmetry in every unit cell. By pumping a digital signal into the metasurface, we investigate the interaction between incident waves and the dynamic metasurface. Experimental results indicate that compact localized states in the nontrivial flat band could enhance the wave-matter interactions to convert more incident waves to time-modulated harmonic photonics. Although our experiments are conducted in the microwave regime, extending the related concepts into the optical plasmonic systems is feasible. Our findings pave an avenue toward planar integrated photonic devices with nontrivial flat bands and exotic transmission phenomena.

关键词： Metamaterials Surface plasmons Topological insulators Electromagnetic wave theory

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Estimating the Composition Ratios of Network Services Carried in Mixed Traffic

SSRN

引用

SSRN 2023年

作者： Xie, Yi Wu, Zihui Tang, Shensheng Liu, Xingcheng School of Computer Science and Engineering Guangdong Key Laboratory of Information Security Sun Yet-sen University Guangzhou510275 China Department of Electrical and Computer Engineering St Cloud State University St Cloud MN56301 United States School of Electronics and Information Technology Sun Yat-sen University Guangzhou510006 China

Network performance management (NPM) and quality of service (QoS) guarantee are the key concerns of network operators and service providers/consumers, respectively. The basis for traffic scheduling is one of the vital elements guiding the implementation of both NPM and QoS assurance. Although traffic identification technologies can theoretically be applied to providing basis for traffic scheduling, the computational complexity caused by the flow-by-flow processing makes them unsuitable for actual large-scale high-throughput network scenarios. In this work, we introduce a new scheme to provide a basis for service-oriented NPM and QoS guarantee. The proposed scheme treats the mixed traffic as a whole and estimates the composition ratios of network services carried in mixed traffic, which makes traffic scheduling for NPM and QoS more reasonable and flexible. To estimate the composition ratios, the observed mixed traffic is expressed as a bipartite graph according to the communication relationship. Then, the bipartite graph is further projected to a multi-dimensional hyper-image based on node coding, random walking and embedding mapping. By this way, we convert the service composition ratio estimation into a problem similar to image classification and enable it to be solved by general machine learning methods like convolutional neural networks. The proposed scheme facilitates batch traffic scheduling and can reorganize the distribution of compositions of network services for each link based on given management strategies. Its computational complexity is significantly lower than that of flow-by-flow processing methods. We validate the proposed solution via real network data and evaluate its performance with some benchmark methods based on traffic identification. The experimental results show that the proposed solution can accurately infer the service composition ratios of mixed traffic with low computational complexity. © 2023, The Authors. All rights reserved.

关键词： Computational complexity

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A Consistency-Based Loss for Deep Odometry Through Uncertainty Propagation

A Consistency-Based Loss for Deep Odometry Through Uncertain...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Hamed Damirchi Roohollah Khorrambakht Hamid D. Taghirad Behzad Moshiri Advanced Robotics and Automated Systems Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering New York University New York USA School of ECE University College of Engineering University of Tehran Tehran Iran

Conventionally, deep odometry networks use objective functions that only penalize short-term deviations from the true path. Since such an objective does not impose any constraints on the long-term deviations from the path, a second consistency-based loss term may be added to lower long-term drift. However, maintaining a balance between the two loss terms is challenging and often treated as a design hyperparameter. To mitigate this balancing issue, we propose to use the uncertainty over both odometry and the long-term transformations in a maximum likelihood setting and allow the network to tune the weighting between the two loss terms. To this end, we derive the odometry uncertainty alongside the pose outputs using the network itself and to derive the covariance matrix over the integrated transformation, we propose to propagate the odometry uncertainty through each iteration. This formulation provides an adaptive and statistically consistent method to weigh the incremental and integrated loss terms against each other, noting the increase in uncertainty as more steps are integrated over. We show that our approach to consistency-based losses allows the network to surpass the accuracy of the state-of-the-art visual odometry approaches. Then, the efficacy of the derived uncertainty as weighting medium is visualized and the performance benefits of uncertainty quantification are shown in a pose-graph based localization scenario.

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Periodic electromagnetic signals as potential precursor for seismic activity

引用

Journal of Central South University 2021年第8期28卷 2463-2471页

作者： YONG Shan-shan WANG Xin-an ZHANG Xing GUO Qin-meng WANG Jing YANG Chao JIANG Bing-hui Key Laboratory of Integrated Micro-Systems Science and Engineering Applications Peking University Shenzhen Graduate SchoolShenzhen 518055China School of Electronics Engineering and Computer Science Peking UniversityBeijing 100871China

Electromagnetic signals may be a promising precursor to seismic activity which has been observed in many case studies in past ***,the correlation and causation between the electromagnetic signals and the seismic activity are still unclear without intensive observation *** order to find seismoelectromagnetic phenomenon,we deployed AETA(acoustic and electromagnetic testing all-in-one system),a high-density multi-component seismic monitoring system in the China Earthquake Science Experiment site(CESE,in Sichuan Province and Yunnan Province,China)and the capital circle(areas with a distance which is≤200 km from Beijing),to record electromagnetic and geo-acoustic data across 0.1 Hz−10 *** the course of data collection,we discovered an electromagnetic waveform that occurs on a daily *** the signal generally coincides with sunrise and sunset,we named this phenomenon the SRSS(Sunrise-Sunset)*** conducting three statistical tests based on seismicity and SRSS,we determined that the SRSS waveform is roughly correlated with the onset of seismic *** generally occurs at the regions where seismicity *** discovery might have significant implications with respect to the future of earthquake prediction.

关键词： seismic precursor periodic electromagnetic signal Sunrise-Sunset(SRSS)waveform

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Measurement-Device-Independent Deterministic Quantum Key Distribution

Measurement-Device-Independent Deterministic Quantum Key Dis...

引用

International Conference on Network and Information systems for computers (ICNISC)

作者： Ting Zhang Jie Liu Guodong Kang School of Physics and Mechanical and Electrical Engineering Jishou University Jishou China School of Computer Science and Engineering & School of Physics and Mechanical and Electrical Engineering Jishou University Jishou China Key Laboratory of Low Dimensional Quantum Structures and Quantum Control of Ministry of Education College of Physics and Electronic Science Hunan Normal University Changsha China

Improve the secure key rate and the limited communication distance is the main goal in the field of quantum key distribution. Measurement-device-independent quantum key distribution, not only removes all detector side channel attacks, but also doubles the secure transmission distance. However, most of measurement-device -independent quantum key distribution protocols are non-deterministic. In this paper, we propose a measurement-device-independent deterministic quantum key distribution protocol that doubles the secure distance and amends the non-deterministic factor of current measurement-device -independent quantum key distribution. And with imperfect devices model assumption, we derived the formula of the performances for it and find that the limited distance can be extended over 200km with relatively high secure key rate by employing parameters of current technologies.

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