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Articles 781 - 810 of 3518
Full-Text Articles in Engineering
Energy-Performance Scalability Analysis Of A Novel Quasi-Stochastic Computing Approach, Prashanthi Metku, Ramu Seva, Minsu Choi
Energy-Performance Scalability Analysis Of A Novel Quasi-Stochastic Computing Approach, Prashanthi Metku, Ramu Seva, Minsu Choi
Electrical and Computer Engineering Faculty Research & Creative Works
Stochastic computing (SC) is an emerging low-cost computation paradigm for efficient approximation. It processes data in forms of probabilities and offers excellent progressive accuracy. Since SC's accuracy heavily depends on the stochastic bitstream length, generating acceptable approximate results while minimizing the bitstream length is one of the major challenges in SC, as energy consumption tends to linearly increase with bitstream length. To address this issue, a novel energy-performance scalable approach based on quasi-stochastic number generators is proposed and validated in this work. Compared to conventional approaches, the proposed methodology utilizes a novel algorithm to estimate the computation time based on …
Bayesian Optimization For High-Speed Channel Equalization, Zurab Kiguradze, Nana Dikhaminjia, Mikheil Tsiklauri, Jiayi He, Bhyrav Mutnury, Arun Chada, James Drewniak
Bayesian Optimization For High-Speed Channel Equalization, Zurab Kiguradze, Nana Dikhaminjia, Mikheil Tsiklauri, Jiayi He, Bhyrav Mutnury, Arun Chada, James Drewniak
Electrical and Computer Engineering Faculty Research & Creative Works
Equalization methods are used to recover the signal attenuated by channel loss. Different optimization algorithms are applied to find the best tap coefficients for each equalization that will improve eye opening and reduce bit error rate. The goal function for most equalization optimization algorithms is to reduce the difference between input and output signals, which is a linear optimization problem and can be solved relatively easily. This indirectly will increase eye height and improve eye diagram. Directly optimizing eye height is a non-linear problem and cannot be solved with analytical method. We are proposing FFE and DFE combined equalization optimization …
Detection And Mitigation Of Attacks In Nonlinear Stochastic System Using Modified Detector, Chandreyee Bhowmick, S. Jagannathan
Detection And Mitigation Of Attacks In Nonlinear Stochastic System Using Modified Detector, Chandreyee Bhowmick, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
A novel attack detection method is presented for a nonlinear system with known dynamics using the measured output in the presence of additive process and measurement noise. False data injection (FDI) and replay attacks are considered using a modified fault detector. The difference between the measured and the estimated output from an adaptive observer, often known as the innovation signal, is generated and shown to have a Gaussian distribution with non-zero mean. This innovation signal in conjunction with the modified detector is utilized to detect attacks under a stable controller using the estimated state vector. Unlike FDI attack, where the …
Neutron Detection Performance Of Gallium Nitride Based Semiconductors, Chuanle Zhou, Andrew G. Melton, Eric Burgett, Nolan Hertel, Ian T. Ferguson
Neutron Detection Performance Of Gallium Nitride Based Semiconductors, Chuanle Zhou, Andrew G. Melton, Eric Burgett, Nolan Hertel, Ian T. Ferguson
Electrical and Computer Engineering Faculty Research & Creative Works
Neutron detection is crucial for particle physics experiments, nuclear power, space and international security. Solid state neutron detectors are of great interest due to their superior mechanical robustness, smaller size and lower voltage operation compared to gas detectors. Gallium nitride (GaN), a mature wide bandgap optoelectronic and electronic semiconductor, is attracting research interest for neutron detection due to its radiation hardness and thermal stability. This work investigated thermal neutron scintillation detectors composed of GaN thin films with and without conversion layers or rare-earth doping. Intrinsic GaN-based neutron scintillators are demonstrated via the intrinsic 14N(n, p) reaction, which has a small …
Strain-Stress Study Of Alxga1−Xn/Ain Heterostructures On C-Plane Sapphire And Related Optical Properties, Yining Feng, Vishal Saravade, Ting Fung Chung, Yongqi Dong, Hua Zhou, Bahadir Kucukgok, Ian T. Ferguson, Na Lu
Strain-Stress Study Of Alxga1−Xn/Ain Heterostructures On C-Plane Sapphire And Related Optical Properties, Yining Feng, Vishal Saravade, Ting Fung Chung, Yongqi Dong, Hua Zhou, Bahadir Kucukgok, Ian T. Ferguson, Na Lu
Electrical and Computer Engineering Faculty Research & Creative Works
This work presents a systematic study of stress and strain of AlxGa1−xN/AlN with composition ranging from GaN to AlN, grown on a c-plane sapphire by metal-organic chemical vapor deposition, using synchrotron radiation high-resolution X-ray diffraction and reciprocal space mapping. The c-plane of the AlxGa1−xN epitaxial layers exhibits compressive strain, while the a-plane exhibits tensile strain. The biaxial stress and strain are found to increase with increasing Al composition, although the lattice mismatch between the AlxGa1−xN and the buffer layer AlN gets smaller. A reduction in the lateral coherence lengths and an increase in the edge and …
Two-Step Enhanced Deep Learning Approach For Electromagnetic Inverse Scattering Problems, He Ming Yao, Wei E.I. Sha, Lijun Jiang
Two-Step Enhanced Deep Learning Approach For Electromagnetic Inverse Scattering Problems, He Ming Yao, Wei E.I. Sha, Lijun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
In this letter, a new deep learning (DL) approach is proposed to solve the electromagnetic inverse scattering (EMIS) problems. The conventional methods for solving inverse problems face various challenges including strong ill-conditions, high contrast, expensive computation cost, and unavoidable intrinsic nonlinearity. To overcome these issues, we propose a new two-step machine learning based approach. In the first step, a complex-valued deep convolutional neural network is employed to retrieve initial contrasts (permittivity's) of dielectric scatterers from measured scattering data. In the second step, the previously obtained contrasts are input into a complex-valued deep residual convolutional neural network to refine the reconstruction …
An Optimal Hybrid Learning Approach For Attack Detection In Linear Networked Control Systems, Haifeng Niu, Avimanyu Sahoo, Chandreyee Bhowmick, S. Jagannathan
An Optimal Hybrid Learning Approach For Attack Detection In Linear Networked Control Systems, Haifeng Niu, Avimanyu Sahoo, Chandreyee Bhowmick, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
A novel learning-based attack detection and estimation scheme is proposed for linear networked control systems NCS, wherein the attacks on the communication network in the feedback loop are expected to increase network induced delays and packet losses, thus changing the physical system dynamics. First, the network traffic flow is modeled as a linear system with uncertain state matrix and an optimal Q-learning based control scheme over finite-horizon is utilized to stabilize the flow. Next, an adaptive observer is proposed to generate the detection residual, which is subsequently used to determine the onset of an attack when it exceeds a predefined …
E-Mobility -- Advancements And Challenges, Aswad Adib, Khurram K. Afridi, Mahshid Amirabadi, Fariba Fateh, Mehdi Ferdowsi, Brad Lehman, Laura H. Lewis, Behrooz Mirafzal, Maryam Saeedifard, Mohammad B. Shadmand, Pourya Shamsi
E-Mobility -- Advancements And Challenges, Aswad Adib, Khurram K. Afridi, Mahshid Amirabadi, Fariba Fateh, Mehdi Ferdowsi, Brad Lehman, Laura H. Lewis, Behrooz Mirafzal, Maryam Saeedifard, Mohammad B. Shadmand, Pourya Shamsi
Electrical and Computer Engineering Faculty Research & Creative Works
Mobile platforms cover a broad range of applications from small portable electric devices, drones, and robots to electric transportation, which influence the quality of modern life. The end-to-end energy systems of these platforms are moving toward more electrification. Despite their wide range of power ratings and diverse applications, the electrification of these systems shares several technical requirements. Electrified mobile energy systems have minimal or no access to the power grid, and thus, to achieve long operating time, ultrafast charging or charging during motion as well as advanced battery technologies are needed. Mobile platforms are space-, shape-, and weight-constrained, and therefore, …
Biomarker Discovery In Inflammatory Bowel Diseases Using Network-Based Feature Selection, Mostafa Abbas, John Matta, Thanh Le, Halima Bensmail, Tayo Obafemi-Ajayi, Vasant Honavar, Yasser El-Manzalawy
Biomarker Discovery In Inflammatory Bowel Diseases Using Network-Based Feature Selection, Mostafa Abbas, John Matta, Thanh Le, Halima Bensmail, Tayo Obafemi-Ajayi, Vasant Honavar, Yasser El-Manzalawy
Electrical and Computer Engineering Faculty Research & Creative Works
Reliable identification of Inflammatory biomarkers from metagenomics data is a promising direction for developing non-invasive, cost-effective, and rapid clinical tests for early diagnosis of IBD. We present an integrative approach to Network-Based Biomarker Discovery (NBBD) which integrates network analyses methods for prioritizing potential biomarkers and machine learning techniques for assessing the discriminative power of the prioritized biomarkers. Using a large dataset of new-onset pediatric IBD metagenomics biopsy samples, we compare the performance of Random Forest (RF) classifiers trained on features selected using a representative set of traditional feature selection methods against NBBD framework, configured using five different tools for inferring …
Data Collection And Analysis Techniques For Solar Car Telemetry Data, Michael Rouse, Miranda Sauer, Kurt Louis Kosbar
Data Collection And Analysis Techniques For Solar Car Telemetry Data, Michael Rouse, Miranda Sauer, Kurt Louis Kosbar
Electrical and Computer Engineering Faculty Research & Creative Works
Data collected from a solar car is monitored in real-time, which allows for intelligent decision making, efficient debugging, and high-quality testing for solar car teams. This paper compares three databases (MySQL, PostgreSQL, and MongoDB) to determine the optimal database system that should be used at solar car competitions. Each database system was tested using simulated solar car data to measure read and write speeds, and quality of performance on a low-power computer. Data were analyzed and displayed with custom interfaces to improve the user experience at solar car competitions.
Neural Network Predictive Controller For Grid-Connected Virtual Synchronous Generator, Sepehr Saadatmand, Mohamad Saleh Sanjari Nia, Pourya Shamsi, Mehdi Ferdowsi, Donald C. Wunsch
Neural Network Predictive Controller For Grid-Connected Virtual Synchronous Generator, Sepehr Saadatmand, Mohamad Saleh Sanjari Nia, Pourya Shamsi, Mehdi Ferdowsi, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a neural network predictive controller is proposed to regulate the active and the reactive power delivered to the grid generated by a three-phase virtual inertia-based inverter. The concept of the conventional virtual synchronous generator (VSG) is discussed, and it is shown that when the inverter is connected to non-inductive grids, the conventional PI-based VSGs are unable to perform acceptable tracking. The concept of the neural network predictive controller is also discussed to replace the traditional VSGs. This replacement enables inverters to perform in both inductive and non-inductive grids. The simulation results confirm that a well-trained neural network …
Heuristic Dynamic Programming For Adaptive Virtual Synchronous Generators, Sepehr Saadatmand, Mohamad Saleh Sanjari Nia, Pourya Shamsi, Mehdi Ferdowsi, Donald C. Wunsch
Heuristic Dynamic Programming For Adaptive Virtual Synchronous Generators, Sepehr Saadatmand, Mohamad Saleh Sanjari Nia, Pourya Shamsi, Mehdi Ferdowsi, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper a neural network heuristic dynamic programing (HDP) is used for optimal control of the virtual inertia-based control of grid connected three-phase inverters. It is shown that the conventional virtual inertia controllers are not suited for non-inductive grids. A neural network-based controller is proposed to adapt to any impedance angle. Applying an adaptive dynamic programming controller instead of a supervised controlled method enables the system to adjust itself to different conditions. The proposed HDP consists of two subnetworks: critic network and action network. These networks can be trained during the same training cycle to decrease the training time. …
Dual Heuristic Dynamic Programing Control Of Grid-Connected Synchronverters, Sepehr Saadatmand, Mohamad Saleh Sanjari Nia, Pourya Shamsi, Mehdi Ferdowsi
Dual Heuristic Dynamic Programing Control Of Grid-Connected Synchronverters, Sepehr Saadatmand, Mohamad Saleh Sanjari Nia, Pourya Shamsi, Mehdi Ferdowsi
Electrical and Computer Engineering Faculty Research & Creative Works
A new approach to control a grid-connected synchronverter by using a dual heuristic dynamic programing (DHP) design is presented. The disadvantages of conventional synchronverter controller such as the challenges to cope with nonlinearity, uncertainties, and non-inductive grids are discussed. To deal with the aforementioned challenges a neural network–based adaptive critic design is introduced to optimize the associated cost function. The characteristic of the neural networks facilitates the performance under uncertainties and unknown parameters (e.g. different power angles). The proposed DHP design includes three neural networks: system NN, action NN, and critic NN. The simulation results compare the performance of the …
Gan-Based Room Temperature Spintronics For Next Generation Low Power Consumption Electronic Devices, Vishal Saravade, Amirhossein Ghods, Andrew P. Woode, Chuanle Zhou, Ian Ferguson
Gan-Based Room Temperature Spintronics For Next Generation Low Power Consumption Electronic Devices, Vishal Saravade, Amirhossein Ghods, Andrew P. Woode, Chuanle Zhou, Ian Ferguson
Electrical and Computer Engineering Faculty Research & Creative Works
There has been an exponential growth in the microelectronics industry over the last 70 years with a consistent miniaturization of transistors' size and increase in the speed and on-chip transistors density with reasonable power consumption, as seen in Figure 1 [1]. This trend will saturate soon especially due to the unintended thermal noise that is dissipated, as the density of transistors on the chips increase and as the corresponding electronics approach their physical limits. There is a need to implement new processing and computing techniques [2] with more compact size, lower power consumption and enhanced performance. Neuromorphic computing mimics the …
Stochastic Partial Inductance For The Power Integrity Analysis By Polynomial Chaos Expansion, Haimi Qiu, Lijun Jiang, Albert Ruehli
Stochastic Partial Inductance For The Power Integrity Analysis By Polynomial Chaos Expansion, Haimi Qiu, Lijun Jiang, Albert Ruehli
Electrical and Computer Engineering Faculty Research & Creative Works
Partial element equivalent circuit (PEEC) model has attracted great interests to overcome challenges in the power integrity analysis. However, the increasing miniaturization in electronics makes the uncertainty effect an ever more central issue to accurately estimate the inductance in the power distribution networks (PDNs) of high-speed PCBs. In this paper, we propose a stochastic partial inductance modeling approach to quantify the stochastic inductance. Specifically, the deterministic partial inductance is re-formulated using the polynomial chaos expansion. Following the Galerkin projection and polynomial orthogonality, stochastic partial inductance is represented by polynomial bases, which significantly reduces the complexity of the system and leads …
Impulse Response For Full Wave Peec Models Avoiding Late Time Instability, Albert E. Ruehli, Luigi Lombardi, Giulio Antonini, Ye Tao, Michel S. Nakhla, Francesco Ferranti
Impulse Response For Full Wave Peec Models Avoiding Late Time Instability, Albert E. Ruehli, Luigi Lombardi, Giulio Antonini, Ye Tao, Michel S. Nakhla, Francesco Ferranti
Electrical and Computer Engineering Faculty Research & Creative Works
Late time instability is a key issue for obtaining time domain solutions using Computational Electromagnetic (CEM) full-wave techniques. However, impulse inputs lead to a convenient way to cascade time domain solutions for many problems. In this paper we show that stable impulse response solutions can be obtained for full-wave PEEC (Partial Element Equivalent Circuit) models which include retarded partial elements. The conventional time stepping technique is replaced by using the so called NILT (Numerical Inverse Laplace Transform) technique. We show that the late time unstable poles in the EM formulation are not excited by the NILT based solution.
Analysis Of Electromagnetic Vortex Beams Using Modified Dynamic Mode Decomposition In Spatial Angular Domain, Yanming Zhang, Menglin L.N. Chen, Li (Lijun) Jun Jiang
Analysis Of Electromagnetic Vortex Beams Using Modified Dynamic Mode Decomposition In Spatial Angular Domain, Yanming Zhang, Menglin L.N. Chen, Li (Lijun) Jun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
The orbital angular momentum (OAM) modes of electromagnetic (EM) beams are utilized for multiplexing in communication systems, where each OAM mode is encoded with data. The OAM index, or the so-called topological charge, identifies each OAM mode. Recently, the amplitude of OAM mode has also been used as another modulation format. Therefore, accurate extraction of not only the OAM index but also the corresponding amplitude is required. In this paper, a modified dynamic mode decomposition (DMD) algorithm is proposed to analyze the OAM modes. We show that accurate topological charges and high-resolution amplitude patterns of both single OAM mode and …
Iot-Based Cyber-Physical Communication Architecture: Challenges And Research Directions, Md Masud Rana, Rui Bo
Iot-Based Cyber-Physical Communication Architecture: Challenges And Research Directions, Md Masud Rana, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
In order to provide intelligent services, the Internet of Things (IoT) facilitates millions of smart cyber-physical devices to be enabled with network connectivity to sense, collect, process, and exchange information. Unfortunately, the traditional communication infrastructure is vulnerable to cyber attacks and link failures, so it is a challenging task for the IoT to explore these applications. In order to begin research and contribute into the IoT-based cyber-physical digital world, one will need to know the technical challenges and research opportunities. In this study, several key technical challenges and requirements for the IoT communication systems are identified. Basically, privacy, security, intelligent …
Editorial: Bio-Inspired Audio Processing, Models And Systems, Shih Chii Liu, John G. Harris, Mounya Elhilali, Malcolm Slaney
Editorial: Bio-Inspired Audio Processing, Models And Systems, Shih Chii Liu, John G. Harris, Mounya Elhilali, Malcolm Slaney
Electrical and Computer Engineering Faculty Research & Creative Works
No abstract provided.
Compact Endfire Coupled-Mode Patch Antenna With Vertical Polarization, Haozhan Tian, Lijun Jiang, Tatsuo Itoh
Compact Endfire Coupled-Mode Patch Antenna With Vertical Polarization, Haozhan Tian, Lijun Jiang, Tatsuo Itoh
Electrical and Computer Engineering Faculty Research & Creative Works
Coupled-mode patch antenna (CMPA) is able to reform the beam by manipulating the phase of the fringing fields at the edges. In this paper, a method is proposed to realize endfire radiation with vertical polarization based on the concept of CMPA. Besides the phase controlled by the coupling, the asymmetric feeding introduces additional phase shift to one of the radiation slots, which makes the beam pointing to the forward endfire direction within the whole band. The ground of the antenna is truncated to be the same size of the top patch, which eliminates the undesired effect of the ground edge …
Output-Constrained Control Of Nonaffine Multiagent Systems With Partially Unknown Control Directions, Bo Fan, Qinmin Yang, Sarangapani Jagannathan, Youxian Sun
Output-Constrained Control Of Nonaffine Multiagent Systems With Partially Unknown Control Directions, Bo Fan, Qinmin Yang, Sarangapani Jagannathan, Youxian Sun
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, an output-constrained control algorithm is presented for the consensus control of a class of unknown nonaffine multiagent systems (MASs) with partially unknown control directions. Our contribution includes a step forward beyond the usual consensus stabilization result to show that the outputs of agents remain within user-defined time-varying constraints. To achieve the new results, an error transformation technique is established to generate an equivalent MAS from the original one. Stabilization and consensus of the transformed agent states ensure both the satisfaction of the time-varying constraints and the consensus of the original agent states. Based on the Nussbaum gain …
Tvs Devices Transient Behavior Modeling Framework And Application To Seed, Li Shen, Shubhankar Marathe, Javad Meiguni, Guangxiao Luo, Jianchi Zhou, David Pommerenke
Tvs Devices Transient Behavior Modeling Framework And Application To Seed, Li Shen, Shubhankar Marathe, Javad Meiguni, Guangxiao Luo, Jianchi Zhou, David Pommerenke
Electrical and Computer Engineering Faculty Research & Creative Works
The transient behavior for four different types of TVS (non-snapback, snapback, spark gap, varistor) is modeled using the same modeling framework. By a 10 ns VF-TLP, the quasi-static I-V curve and the transient turn-on are captured and modeled in ADS. The models are applied in a SEED simulation to investigate the strengths and weaknesses of the modeling frame.
Discontinuous Galerkin Vs. Ie Method For Electromagnetic Scattering From Composite Metallic And Dielectric Structures, Y.-Y. Zhu, Q.-M. Cai, R. Zhang, X. Cao, Y.-W. Zhao, B. Gao, Jun Fan
Discontinuous Galerkin Vs. Ie Method For Electromagnetic Scattering From Composite Metallic And Dielectric Structures, Y.-Y. Zhu, Q.-M. Cai, R. Zhang, X. Cao, Y.-W. Zhao, B. Gao, Jun Fan
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, an efficient volume surface integral equation (VSIE) method with nonconformal discretization is developed for the analysis of electromagnetic scattering from composite metallic and dielectric (CMD) structures. This VSIE scheme utilizes curved tetrahedral (triangular) elements for volume (surface) modeling and the associated CRWG (CSWG) basis functions for volume current (surface) current modeling. Further, a discontinuous Galerkin (DG) volume integral equation (VIE) method and a DG surface integral equation (SIE) approach are adopted for dielectric and metallic parts, respectively, which allow both conformal and nonconformal volume/surface discretization improving meshing flexibility considerably. Numerical results are provided to demonstrate the accuracy, …
Control Of A Three-Phase Grid-Connected Inverter Under Non-Ideal Grid Conditions With Online Parameter Update, Vikram Roy Chowdhury, Jonathan W. Kimball
Control Of A Three-Phase Grid-Connected Inverter Under Non-Ideal Grid Conditions With Online Parameter Update, Vikram Roy Chowdhury, Jonathan W. Kimball
Electrical and Computer Engineering Faculty Research & Creative Works
Three-phase grid-connected inverter modeling depends on the equivalent resistance and inductance between the inverter and the grid. However, these parameters are not fixed during the operation of the inverter and vary with the operating conditions. In this paper, a new globally stable adaptive controller is proposed to estimate these values online and update the controller during its operation. A model reference adaptive system (MRAS) based on two fictitious quantities with no physical significance is utilized, namely M = v · i∗ and N = v∗ x i, where v and i are the steady-state values of voltage and current in …
Machine Learning Methodology Review For Computational Electromagnetics, He Ming Yao, Lijun Jiang, Huan Huan Zhang, Wei E.I. Sha
Machine Learning Methodology Review For Computational Electromagnetics, He Ming Yao, Lijun Jiang, Huan Huan Zhang, Wei E.I. Sha
Electrical and Computer Engineering Faculty Research & Creative Works
While machine learning is revolutionizing every corner of modern technologies, we have been attempting to explore whether machine learning methods could be used in computational electromagnetic (CEM). In this paper, five efforts in line with this direction are reviewed. They include forward methods such as the method of moments (MoM) solved by the artificial neural network training process, FDTD PML (perfectly matched layer) using the hyperbolic tangent basis function (HTBF), etc. There are also inverse problems that use the deep ConvNets for the effective source reconstruction and subwavelength imaging in the far-field. Benchmarks are provided to demonstrate the feasibility of …
Cascaded Fabry-Pérot Interferometers With Vernier Effect For Gas Pressure Measurement, Hongfeng Lin, Yanyan Xu, Farhan Mumtaz, Yutang Dai, Ai Zhou
Cascaded Fabry-Pérot Interferometers With Vernier Effect For Gas Pressure Measurement, Hongfeng Lin, Yanyan Xu, Farhan Mumtaz, Yutang Dai, Ai Zhou
Electrical and Computer Engineering Faculty Research & Creative Works
A sensitivity enhanced gas pressure sensor with Vernier effect is proposed in this paper. The sensor is a cascade configuration which includes two Fabry-Pérot interferometers (FPIs) with different free spectrum range (FSR). Each Fabry-Pérot interferometer is fabricated by inserting a piece of hollow core fiber (HCF) in between two sections of single mode fiber (SMF). Femtosecond laser is applied for drilling an opening on the HCF of sensing FPI to make the air hole interact with outside environment, while the air hole of the reference FPI is kept closed. Gas pressure response is measured by monitoring the wavelength shift of …
Generalizing Multiple Access Wiretap And Wiretap Ii Channel Models: Achievable Rates And Cost Of Strong Secrecy, Mohamed Nafea, Aylin Yener
Generalizing Multiple Access Wiretap And Wiretap Ii Channel Models: Achievable Rates And Cost Of Strong Secrecy, Mohamed Nafea, Aylin Yener
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, new two-user multiple access wiretap channel models are studied. First, the multiple access wiretap channel II with a discrete memoryless main channel under different wiretapping scenarios is introduced. The wiretapper, as in the classical wiretap channel II model, chooses a fixed-size subset of the channel uses, in which it obtains noise-free observations of one of the codewords: a deterministic function, e.g., superposition, of the two codewords or each of the two codewords. A fourth wiretapping scenario is considered, in which the wiretapper, in each position it chooses, decides to observe either one of the codewords or both …
Detection Of Sensor Attacks In Uncertain Stochastic Linear Systems, Chandreyee Bhowmick, S. Jagannathan
Detection Of Sensor Attacks In Uncertain Stochastic Linear Systems, Chandreyee Bhowmick, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
A novel attack detection scheme is developed for linear discrete-time systems with unknown dynamics that are subject to the additive process and output measurements noise. A novel stochastic adaptive observer is proposed to estimate the state vector in the presence of noisy sensor measurements and uncertain dynamics, and also to generate the innovation signal to detect attacks using a modified $\chi2} $ detector. It has been shown that the innovation signal, which is defined as the difference between the measured and the estimated output from the observer, has a Gaussian distribution with non-zero mean. The modified $\chi^ {2} $ detector …
Attack Detection In Linear Networked Control Systems By Using Learning Methodology, Haifeng Niu, A. Sahoo, C. Bhowmick, S. Jagannathan
Attack Detection In Linear Networked Control Systems By Using Learning Methodology, Haifeng Niu, A. Sahoo, C. Bhowmick, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
A novel learning-based attack detection scheme for linear networked control systems (NCS) is introduced. The class of attacks considered here tends to increase network induced delays and packet losses which affects the physical system dynamics. For the network side, an adaptive observer is proposed to generate the attack detection residual, which in turn is utilized to determine the onset of an attack when it exceeds a predefined threshold. The uncertain stochastic physical system dynamics as a result of network-induced delays of packet losses require an optimal Q-learning based event-triggered controller that optimizes the control policy and the event-triggering instants simultaneously. …
Microwave Reflectometry For Physical Inspections, Mohammad Tayeb Ahmad Ghasr, R. Zoughi, Satyajeet Shinde, Sasi Jothibasu
Microwave Reflectometry For Physical Inspections, Mohammad Tayeb Ahmad Ghasr, R. Zoughi, Satyajeet Shinde, Sasi Jothibasu
Electrical and Computer Engineering Faculty Research & Creative Works
Utilizing microwave reflections to compare a reference device with counterfeit and/or aging devices under test. The reflection from the device under test varies based on certain properties, which results in each device having a unique and intrinsic electromagnetic signature. Comparisons of the electromagnetic signature of the device under test to the electromagnetic signature of a reference device enable evaluating the acceptability of the device under test.