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arXiv 2021年

作者： Gültekin, Yunus Can Alvarado, Alex Vassilieva, Olga Kim, Inwoong Palacharla, Paparao Okonkwo, Chigo Willems, Frans M.J. Information and Communication Theory Lab Signal Processing Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven5600 MB Netherlands Electro-Optical Communications Group Institute for Photonics Integration Department of Electrical Engineering Eindhoven University of Technology Eindhoven5600 MB Netherlands Fujitsu Network Communications Inc. RichardsonTX75082 United States

Nonlinear interference (NLI) generated during the propagation of an optical waveform through the fiber depends on the fourth order standardized moment of the channel input distribution, also known as kurtosis. Probabilistically-shaped inputs optimized for the linear Gaussian channel have a Gaussian-like distribution with high kurtosis. For optical channels, this leads to an increase in NLI power and consequently, a decrease in effective signal-to-noise ratio (SNR). In this work, we propose kurtosis-limited enumerative sphere shaping (K-ESS) as an algorithm to generate low-kurtosis shaped inputs. Numerical simulations at a shaping blocklength of 108 amplitudes demonstrate that with K-ESS, it is possible to increase the effective SNRs by 0.4 dB in a single-span single-channel scenario at 400 Gbit/s. K-ESS offers also a twofold decrease in frame error rate with respect to Gaussian-channel-optimal sphere shaping. Copyright © 2021, The Authors. All rights reserved.

关键词： Higher order statistics

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Yule-Walker Equations Using Higher Order Statistics for Nonlinear Autoregressive Model

Yule-Walker Equations Using Higher Order Statistics for Nonl...

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2019 signal processing Symposium, SPSympo 2019

作者： Libal, Urszula Johansson, Karl H. School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Signal Processing Systems Department Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (纸本)9781728117157

The paper presents the derivation of Yule-Walker equations for the nonlinear autoregressive model NAR(p) of a time-series. The proposed method allows for easy calculation of parameters of the model. In the determined equations, higher order statistics are used, instead of autocovariances. For the linear autoregressive model AR(p), the standard Yule-Walker equations are directly based on autocovariances of time-series, or equivalently autocorrelations if the equations are rescaled. Unfortunately, it does not apply for nonlinear model. The authors show a compact matrix notation of Yule-Walker equations for the nonlinear autoregressive model with the nonlinearity of polynomial type of degree 2, with the use of higher order statistics up to 4th order, and numerical examples for electromyography signals for different hand movements. © 2019 IEEE.

关键词： Time series

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Optimum elements selection in IRS-assisted UAV communications with phase errors

TechRxiv

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TechRxiv 2021年

作者： Jangsher, Sobia Al-Dweik, Arafat Al-Jarrah, Mohammd Ahmad Alusa, Emad Alouini, Mohamed-Slim Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates Wireless and Signal Processing Lab Institute of Space Technology Islamabad Pakistan School of Electrical and Electronic Engineering University of manchester ManchesterM13 9PL United Kingdom Center for Cyber Physical Systems Khalifa University Abu Dhabi United Arab Emirates Department of Electrical and Computer Engineering Western University LondonON Canada Thuwal Makkah Province Saudi Arabia

This letter considers minimizing the bit error rate (BER) of unmanned aerial vehicle (UAV) communications assisted by intelligent reflecting surfaces (IRSs). By noting that increasing the number of IRS elements in the presence of phase errors does not necessarily improve the BER, it is crucial to use only the elements that contribute to reducing the BER. Consequently, we propose an efficient algorithm to activate only the elements that improve the BER. The proposed algorithm has lower complexity and comparable BER to the optimum selection process, which is an NP-hard problem. The accuracy of the estimated phase is evaluated by deriving the probability distribution function (PDF) of the least-square (LS) channel estimator, and showing that the PDF can be closely approximated by the von Mises distribution at high signal-to-noise ratios (SNRs). The obtained analytical and simulation results show that using all the available reflectors can significantly deteriorate the BER, and thus, elements’ selection is necessary. In particular scenarios, using about 26% of the reflectors provides more than 10 fold BER reduction. © 2021, CC BY.

关键词： Bit error rate

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P13.10.A NORADRENERGIC AGONISTS AS NEW TREATMENT OPPORTUNITY AGAINST RADIATION-INDUCED COGNITIVE DECLINE

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Neuro-Oncology 2024年第SUPPLEMENT_5期26卷 v73–v74页

作者： De Bie, I Berden, L Peeters, B Vanhove, C Boterberg, T Tabury, K Primac, I Raedt, R Benotmane, R 4BRAIN Department of Head and Skin Faculty of Medicine and Health sciences Ghent University Ghent Belgium Radiobiology Unit Nuclear Medical Application Institute Belgian Nuclear Research Centre (SCK CEN) Mol Belgium Medical Image and Signal Processing (MEDISIP) Department of Electronics and Information systems Faculty of Engineering and Architecture Ghent University Ghent Belgium Department of Radiation Oncology Ghent University hospital Ghent Belgium

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Optimal Sampling & Reconstruction: Theory and Applications

arXiv

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arXiv 2019年

作者： Haldar, Justin Signal and Image Processing Institute Ming Hsieh Department of Electrical and Computer Engineering University of Southern California

The optimization of MRI data sampling and image reconstruction methods has been a priority for the MRI community since the very early days of the field. Designing an "optimal" method requires the definition of an optimality metric (i.e., a quantitative evaluation of the "goodness" of different competing approaches that allows an objective comparison between them). However, a key challenge is that there are many different possible ways of quantitatively evaluating the "goodness" of a data sampling scheme or a reconstruction result, and there are no acquisition or reconstruction methods that are known to be universally optimal with respect to all of these possible metrics simultaneously. Thus, optimization of MRI methods requires a subjective choice about what aspects of quality matter most in the context of a given MRI experiment, and subsequently the subjective choice of an optimality metric that hopefully does a reasonable job of quantifying those aspects of quality. Once these choices are made, the optimization problem becomes well-defined, and it remains to choose an algorithm that can identify data sampling or image reconstruction methods that are optimal with respect to the chosen metric. All of these choices are generally nontrivial. Copyright © 2019, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Coupling of Planar Waveguide Modes in All-Dielectric Multilayer Structures: Monitoring the Dependence of Local Electric Fields on the Coupling Strength

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Physical Review Applied 2021年第6期16卷 064065-064065页

作者： Kengo Motokura Minoru Fujii Dmitry V. Nesterenko Zouheir Sekkat Shinji Hayashi Department of Electrical and Electronic Engineering Graduate School of Engineering Kobe University Kobe 657-8501 Japan Image Processing Systems Institute RAS - Branch of the FSRC “Crystallography and Photonics” RAS Samara 443001 Russia Faculty of Information Technology Samara National Research University Samara 443086 Russia Optics and Photonics Center Moroccan Foundation for Science Innovation and Research (MAScIR) University Mohammed VI Polytechnic Rabat 10100 Morocco Faculty of Sciences Mohamed V University in Rabat Rabat 10010 Morocco Graduate School of Engineering Osaka University Osaka 585-0871 Japan

Except for a few cases to which sophisticated techniques are applicable, it is difficult to observe experimentally local electric fields or near fields associated with excitation of electromagnetic modes supported by building blocks of nanostructures. Although elucidating the behavior of the local electric fields or near fields is very useful to develop potential applications of the nanostructures, in many cases, their behaviors have been only speculated from simulations based on the electromagnetic theory. Here, we develop a simple technique that allows us to study experimentally the average behavior of the local electric fields inside two planar waveguide layers interacting with each other in all-dielectric multilayer structures. The study is made possible by doping the two waveguide layers with two different fluorophores. Fluorescence intensities detected at two different wavelengths allow us to study separately the behaviors of the local electric fields inside each waveguide layer. Angle-scan fluorescence excitation spectra are measured for two different series of multilayer samples by exciting the samples in an attenuated total reflection geometry. The line shapes observed are in good agreement with theoretical ones calculated based on the electromagnetic theory, confirming that the experimental fluorescence excitation spectra reflect well the average behaviors of the local electric fields. Applying the developed technique, we investigate systematically the changes in the local electric fields inside the waveguide layers caused by the change in the strength of coupling between the two waveguide modes. In one series of the samples, a gradual transition in the behavior of the local electric fields, from a Fano-resonant behavior to a double-peak behavior, is demonstrated with increasing the coupling strength. In another series of the samples, the coupling strength is widely changed and the formation of the coupled modes in a strong coupling regime is clearly obser

关键词： Luminescence Metrology Nanophotonics Coupled oscillators Dielectrics Multilayer thin films Waveguides Fluorescence spectroscopy

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One-dimensional quasi bound states in the continuum with large operation bandwidth in the ω~k space for nonlinear optical applications

arXiv

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arXiv 2022年

作者： Sun, Kaili Jiang, Hui Bykov, Dmitry A. Van, Vien Levy, Uriel Cai, Yangjian Han, Zhanghua Shandong Provincial Key Laboratory of Optics and Photonic Devices Center of Light Manipulation and Applications School of Physics and Electronics Shandong Normal University Jinan250358 China Image Processing Systems Institute Branch of the Federal Scientific Research Centre "Crystallography and Photonics" Russian Academy of Sciences 151 Molodogvardeyskaya st. Samara443001 Russia Department of Electrical and Computer Engineering University of Alberta EdmontonT6G 2V4 Canada Department of Applied Physics The center for Nanoscience and Nanotechnology The Hebrew University of Jerusalem Jerusalem Israel

The phenomenon of bound state in the continuum (BIC) with infinite quality factor and lifetime has emerged in recent years in photonics as a new tool of manipulating light-matter interactions. However, most of the investigated structures only support BIC resonances at very few discrete points in the ω~k space. Even when the BIC is switched to a quasi-BIC(QBIC) resonance through perturbation, its frequency will still be located within a narrow spectral band close to that of the original BIC, restricting their applications in many fields where random or multiple input frequencies beyond the narrow band are required. In this work, we demonstrate that a new set of QBIC resonances can be supported by making use of a special binary grating consisting of two alternatingly aligned ridge arrays with the same period and zero-approaching ridge width difference on a slab waveguide. These QBIC resonances are distributed continuously over a broad band along a line in the ω~k space and can thus be considered as one-dimensional QBICs. With the Q factors generally affected by the ridge difference, it is now possible to choose arbitrarily any frequencies on the dispersion line to achieve significantly enhanced light-matter interactions, facilitating many applications where multiple input wavelengths are required, e.g. sum or difference frequency generations in nonlinear optics. Copyright © 2022, The Authors. All rights reserved.

关键词： Resonance

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Converting Neural Networks to Rule Foam

Converting Neural Networks to Rule Foam

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Akash Kumar Panda Bart Kosko Department of Electrical and Computer Engineering Signal and Image Processing Institute University of Southern California Los Angeles California

ISBN: (数字)9781728155845

ISBN: (纸本)9781728155852

A system of rules can approximate a trained neural classifier after sampling from that classifier. The rules define a generalized probability mixture that then describes the classifier. The size or granularity of the rule if-parts defines a foam-like structure with a few large rule if-part set bubbles in patternclass centers and many smaller if-part sets near class borders. The rule foam's mixture gives a Bayesian posterior over the rules. The posterior describes the relative importance of each rule for each observed input and output. The foam's mixture also gives the conditional variance that measures the uncertainty in its output. So the rule base is statistically interpretable as well as modular and adaptive. A rule foam with 1000 Gaussian rules approximated a 96.85% accurate MNIST neural classifier and had itself 95.66% classification accuracy. Foams can also approximate other foams. Some approximator foams out-performed the target foam that generated their training data. The rule foam's granularity mitigates the rule explosion inherent in the rule-based approximator's graph-covering structure.

关键词： Additives Neural networks Bayes methods Dispersion Uncertainty Fuzzy systems Vector quantization

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Noise can speed Markov chain Monte Carlo estimation and quantum annealing

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Physical Review E 2019年第5期100卷 053309-053309页

作者： Brandon Franzke Bart Kosko Center for Quantum Information Science and Technology Signal and Image Processing Institute Department of Electrical and Computer Engineering University of Southern California Los Angeles California 90089 USA

Carefully injected noise can speed the average convergence of Markov chain Monte Carlo (MCMC) estimates and simulated annealing optimization. This includes quantum annealing and the MCMC special case of the Metropolis-Hastings algorithm. MCMC seeks the solution to a computational problem as the equilibrium probability density of a reversible Markov chain. The algorithm must cycle through a long burn-in phase until it reaches equilibrium because the Markov samples are statistically correlated. The special injected noise reduces this burn-in period in MCMC. A related theorem shows that it reduces the cooling time in simulated annealing. Simulations showed that optimal noise gave a 76% speed-up in finding the global minimum in the Schwefel optimization benchmark. The noise-boosted simulations found the global minimum in 99.8% of trials compared with only 95.4% of trials in noiseless simulated annealing. Simulations also showed that the noise boost is robust to accelerated cooling schedules and that noise decreased convergence times by more than 32% under aggressive geometric cooling. Molecular dynamics simulations showed that optimal noise gave a 42% speed-up in finding the minimum potential energy configuration of an eight-argon-atom gas system with a Lennard-Jones 12-6 potential. The annealing speed-up also extends to quantum Monte Carlo implementations of quantum annealing. Noise improved ground-state energy estimates in a 1024-spin simulated quantum annealing simulation by 25.6%. The quantum noise flips spins along a Trotter ring. The noisy MCMC algorithm brings each Markov step closer on average to equilibrium if an inequality holds between two expectations. Gaussian or Cauchy jump probabilities reduce the noise-benefit inequality to a simple quadratic inequality. Simulations show that noise-boosted simulated annealing is more likely than noiseless annealing to sample high probability regions of the search space and to accept solutions that increase the search bre

关键词： Fluctuations & noise Noise

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Bayes Theorem Extends to Overlapping Hypotheses

Bayes Theorem Extends to Overlapping Hypotheses

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Bart Kosko Department of Electrical and Computer Engineering Signal and Image Processing Institute University of Southern California Los Angeles California

ISBN: (数字)9781728155845

ISBN: (纸本)9781728155852

Bayes theorem extends to arbitrary overlapping hypotheses if a local probability describes the inherent uncertainty of each element in the overlap. This local probability avoids over-counting the overlap regions. It arises by normalizing the indicator function of each set hypothesis in the partition by the sum or integral of all the partition indicator functions. The default probability is that an element belongs equally likely to each overlapping hypothesis that contains it. This reduces to a trivial binary distribution in the extreme case of an exact partition with no overlap. The resulting fuzzy or uncertainty-weighted set events give a generalized theorem on total probability. This result gives in turn a Bayes theorem for any partition or collection of overlapping hypotheses. Applications include the overlapping pattern data that trains deep classification networks.

关键词： Uncertainty Fuzzy sets Weight measurement Machine learning Probability distribution Measurement uncertainty Scientific computing

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