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An Online Plug-and-Play Algorithm for Regularized Image Reconstruction

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arXiv 2018年

作者： Sun, Yu Wohlberg, Brendt Kamilov, Ulugbek S. Department of Computer Science and Engineering Washington University in St. Louis MO63130 United States Los Alamos National Laboratory Theoretical Division Los AlamosNM87545 United States Department of Electrical and Systems Engineering Washington University in St. Louis MO63130 United States

Plug-and-play priors (PnP) is a powerful framework for regularizing imaging inverse problems by using advanced denoisers within an iterative algorithm. Recent experimental evidence suggests that PnP algorithms achieve state-of-the-art performance in a range of imaging applications. In this paper, we introduce a new online PnP algorithm based on the iterative shrinkage/thresholding algorithm (ISTA). The proposed algorithm uses only a subset of measurements at every iteration, which makes it scalable to very large datasets. We present a new theoretical convergence analysis, for both batch and online variants of PnP-ISTA, for denoisers that do not necessarily correspond to proximal operators. We also present simulations illustrating the applicability of the algorithm to image reconstruction in diffraction tomography. The results in this paper have the potential to expand the applicability of the PnP framework to very large and redundant datasets. Copyright © 2018, The Authors. All rights reserved.

关键词： Image reconstruction

Convolutional Neural Networks for Epileptic Seizure Prediction

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arXiv 2018年

作者： Eberlein, Matthias Hildebrand, Raphael Tetzlaff, Ronald Hoffmann, Nico Kuhlmann, Levin Brinkmann, Benjamin Müller, Jens Technische Universität Dresden Faculty of Electrical and Computer Engineering Institute of Circuits and Systems Dresden01062 Germany Technische Universität Dresden Faculty of Computer Science Computer Graphics and Visualisation Dresden01062 Germany Faculty of Information Technology Monash University VIC Clayton3800 Australia Department of Medicine St Vincent's Hospital Melbourne VIC Fitzroy3065 Australia Mayo Systems Electrophysiology Laboratory Departments of Neurology and Biomedical Engineering Mayo Clinic RochesterMN55905 United States

Epilepsy is the most common neurological disorder and an accurate forecast of seizures would help to overcome the patient's uncertainty and helplessness. In this contribution, we present and discuss a novel methodology for the classification of intracranial electroencephalography (iEEG) for seizure prediction. Contrary to previous approaches, we categorically refrain from an extraction of hand-crafted features and use a convolutional neural network (CNN) topology instead for both the determination of suitable signal characteristics and the binary classification of preictal and interictal segments. Three different models have been evaluated on public datasets with long-term recordings from four dogs and three patients. Overall, our findings demonstrate the general applicability. In this work we discuss the strengths and limitations of our methodology. Copyright © 2018, The Authors. All rights reserved.

关键词： Electroencephalography

Low-Frequency Noise in Terahertz Plasmonic Field Effect Transistor Sensors

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Low-Frequency Noise in Terahertz Plasmonic Field Effect Tran...

IEEE Sensors Conference

作者： M. S. Shur X. Liu S. Rumyantsev G. Rupper S. Rudin Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Army Research Laboratory

ISBN: (纸本)9781509010134

Terahertz (THz) plasmonic field effect transistor sensors have emerged as prime contenders for applications in THz and sub-THz communications, biomedical sensing, and imaging. Noise is one of the most important factors determining their performance. We show that the conventional approach of using thermal noise of the device impedance for predicting the sensor performance is inadequate because it ignores the effect of the input circuit and (for very short, submicron devices) ignores a very strong effect of the ballistic or quasi-ballistic transport on the device performance.

关键词： Terahertz Plasmonic sensor Noise Ballistic transport terahertz ballistic transport Low-frequency noise input circuits Noise Field effect transistors equipment performance Frequency noise Sensors Thermal noise

Adaptive Energy Management System with a BESS through Experimental-Based Cell Modeling And Adaptive Model Predictive Control

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Adaptive Energy Management System with a BESS through Experi...

IEEE Innovative Smart Grid Technologies - Asia

作者： Byungchul Kim Younggeun Kim Chulho Shin Ross Baldick Power Research Institute Ls Industrial Systems Seoul South Korea Department of Electrical and Computer Engineering University of Texas at Austin Austin USA

ISBN: (纸本)9781538642924

Controlling the estimated state of charge (SOC) for battery energy storage systems (BESSs) is the main challenge behind increasing lithium-ion battery use in home energy management systems (HEMSs). This paper proposes a BESS EMS control strategy considering a dynamic battery model with second-order RC and a nonlinear adaptive unscented Kalman filter (AUKF) state estimation to control HEMSs. The battery model with second-order RC uses open-circuit-voltage over SOC and parameter identification so that the EMS meets a nonlinear model state estimation for model predictive control (MPC). The AUKF algorithm is used to improve reliable and accurate data-based SOC estimation. Adaptive MPC is utilized to achieve optimal power and voltage allocation control of home appliance energy usage via BESSs. The effectiveness of the proposed control strategy is verified through simulation to achieve optimal control of a BESS within a given SOC and to meet data of home power usage patterns.

关键词： Battery energy storage system (BESS) Energy management control Model predictive control (MPC) State estimation Dynamic battery model

Modeling and simulation of air-gapped current transformer based on Preisach Theory

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Protection and Control of Modern power systems 2017年第1期2卷 111-121页

作者： Ya Hui Wu Xin Zhou Dong Sohrab Mirsaeidi State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

Current Transformer(CT)modeling,by which CT’s characteristics can be studied has a significant importance in CT selection and *** spite of numerous studies about closed-core CT model,only a few works have been conducted on air-gapped ones with the following problems:models of which required data is easily-accessible,have poor simulations of magnetization process;on the contrary,models which have satisfactory simulations,are hard to be established because of the hard-to-get required ***,based on Preisach Theory,a novel air-gapped CT model is deduced from the closed core CT *** proposed model is accurate and can be established *** saturation and remanence properties of closed-core CT and air-gapped CT are simulated and compared.

关键词： CT modeling Air gap Preisach Theory Saturation Remanence

Plug-in stochastic gradient method

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arXiv 2018年

作者： Sun, Yu Wohlberg, Brendt Kamilov, Ulugbek S. Department of Computer Science and Engineering Washington University St. LouisMO63130 United States Los Alamos National Laboratory Theoretical Division Los AlamosNM87545 United States Department of Electrical and Systems Engineering Washington University St. LouisMO63130 United States

Plug-and-play priors (PnP) is a popular framework for regularized signal reconstruction by using advanced denoisers within an iterative algorithm. In this paper, we discuss our recent online variant of PnP [1] that uses only a subset of measurements at every iteration, which makes it scalable to very large datasets. We additionally present novel convergence results for both batch and online PnP algorithms. Copyright © 2018, The Authors. All rights reserved.

关键词： Large dataset

Behavior, Modeling and Damping of a New Type of Resonance Involving Type-Ill Wind Turbines

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Behavior, Modeling and Damping of a New Type of Resonance In...

IEEE Workshop on Control and Modeling for power Electronics

作者： Ignacio Vieto Gunaghui Li Jian Sun Depart. Electrical Computer & Systems Engineering Rensselaer Polytechnic Institute Renewable Energy Research Center China Electric Power Research Institute

ISBN: (纸本)9781538655429

A new type of resonance has been identified involving DFIG type wind turbines and inductive grids. This is different from other resonance involving DFIG wind turbines as there is no series compensation, the frequency of resonance is close to the fundamental, and the resonance is accompanied by a second frequency that is mirrored to it with respect to the fundamental. This work explores this resonance through the use of impedance models of the wind turbine. The impedance models used in this work are improved version of previously reported models, the models used in this work consider the dc bus dynamics and the coupling that occurs across the converters due to the non ideal dc voltage. These new impedance models can also take into account the mirrored harmonic frequency currents that arise due to the nonlinear nature of the turbine. A representative case is studied using the new impedance models, and the resonance is found to be due to the interaction between the turbine and grid impedances at a single frequency. The additional current is present only due to the nonlinear nature of the turbine and its due to the coupling over frequency. Finally, an active damper was proposed to eliminate the resonance and shown through simulations to be effective.

关键词： Resonance analysis Subsynchronous resonance Wind turbines Impedance modeling Damping

Context-aware group buying in ultra-dense small cell networks: Unity is strength

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arXiv 2018年

作者： Zhang, Yuli Xu, Yuhua Anpalagan, Alagan Wu, Qihui Xu, Yitao Sun, Youming Feng, Shuo Luo, Yunpeng College of Communications Engineering Army Engineering University of the PLA Nanjing210007 China Science and Technology on Communication Networks Laboratory Shijiazhuang050002 China Department of Electrical and Computer Engineering Ryerson University Toronto Canada College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Cognitive Systems Laboratory McMaster University HamiltonONL8S 4L8 Canada

The ultra-dense small cell networks (SCNs) have been regarded as a promising technology to solve the data traffic explosion in future. However, the complicated relationships among large scale users and cells practically demand a cooperative grouping mechanism to account for the shortage of resources in SCNs. Then, a group buying market mechanism provides a win-win situation and an effective resource allocation in the view of economics. With additional decision information being provided, the context awareness enhances and improves the group buying mechanism. In this article, we propose a Context-Aware Group Buying (CAGB) mechanism to allocate the resources in ultra-dense SCNs. The feasibility, necessity, and effectiveness of CAGB are analyzed first. Then, we introduce the group buying mechanism and some common context awareness. The relationship between context awareness and group buying is also analyzed. Some important technologies in SCNs are discussed in the view of CAGB, such as load balancing, spectrum management, and cooperative caching. Then, the graphical coalition formation games (CFGs) of CAGB are also presented to match the complicated network topologies in SCNs. Two CAGB-based use cases about spectrum market and cooperative caching are presented. Finally, future research issues about context awareness, grouping mechanism, and buying mechanism are discussed. Copyright © 2018, The Authors. All rights reserved.

关键词： Cytology

One-Bit precoding and constellation range design for massive MIMO with QAM Signaling

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arXiv 2018年

作者： Sohrabi, Foad Liu, Ya-Feng Yu, Wei Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto TorontoONM5S3G4 Canada State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific Engineering Computing Academy of Mathematics Systems Science Chinese Academy of Sciences Beijing100190 China

The use of low-resolution digital-to-analog converters (DACs) for transmit precoding provides crucial energy efficiency advantage for massive multiple-input multiple-output (MIMO) implementation. This paper formulates a quadrature amplitude modulation (QAM) constellation range and one-bit symbol-level precoding design problem for minimizing the average symbol error rate (SER) in downlink massive MIMO transmission. A tight upper-bound for SER with low-resolution DAC precoding is first derived. The derived expression suggests that the performance degradation of one-bit precoding can be interpreted as a decrease in the effective minimum distance of the QAM constellation. Using the obtained SER expression, we propose a QAM constellation range design for the singleuser case. It is shown that in the massive MIMO limit, a reasonable choice for constellation range with one-bit precoding is that of the infinite-resolution precoding with per-symbol power constraint, but reduced by a factor of p 2/π or about 0:8. The corresponding minimum distance reduction translates to about 2dB gap between the performance of one-bit precoding and infinite-resolution precoding. This paper further proposes a low-complexity heuristic algorithm for one-bit precoder design. Finally, the proposed QAM constellation range and precoder design are generalized to the multi-user downlink. We propose to scale the constellation range for infinite-resolution zero-forcing (ZF) precoding with per-symbol power constraint by the same factor of p 2/π for one-bit precoding. The proposed one-bit precoding scheme is shown to be within 2dB of infinite-resolution ZF. In term of number of antennas, one-bit precoding requires about 50% more antennas to achieve the same performance as infinite-resolution precoding. Copyright © 2018, The Authors. All rights reserved.

关键词： Quadrature amplitude modulation