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Articles 241 - 270 of 3518
Full-Text Articles in Engineering
Optimal Trajectory Tracking For Uncertain Linear Discrete-Time Systems Using Time-Varying Q-Learning, Maxwell Geiger, Vignesh Narayanan, Sarangapani Jagannathan
Optimal Trajectory Tracking For Uncertain Linear Discrete-Time Systems Using Time-Varying Q-Learning, Maxwell Geiger, Vignesh Narayanan, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This Article Introduces a Novel Optimal Trajectory Tracking Control Scheme Designed for Uncertain Linear Discrete-Time (DT) Systems. in Contrast to Traditional Tracking Control Methods, Our Approach Removes the Requirement for the Reference Trajectory to Align with the Generator Dynamics of an Autonomous Dynamical System. Moreover, It Does Not Demand the Complete Desired Trajectory to Be Known in Advance, Whether through the Generator Model or Any Other Means. Instead, Our Approach Can Dynamically Incorporate Segments (Finite Horizons) of Reference Trajectories and Autonomously Learn an Optimal Control Policy to Track Them in Real Time. to Achieve This, We Address the Tracking Problem …
Profitability Analysis Of Time-Restricted Double-Spending Attack On Pow-Based Large Scale Blockchains With The Aid Of Multiple Attacks, Yiming Jiang, Jiangfan Zhang
Profitability Analysis Of Time-Restricted Double-Spending Attack On Pow-Based Large Scale Blockchains With The Aid Of Multiple Attacks, Yiming Jiang, Jiangfan Zhang
Electrical and Computer Engineering Faculty Research & Creative Works
We consider the time-restricted double-spending attack (TR-DSA) on the Proof-of-Work-based blockchain, where an adversary conducts a DSA within a finite timeframe and simultaneously launches multiple types of attacks on the blockchain. To be specific, the adversary can conduct attacks to isolate some honest miners and cause block propagation delays among miners to enhance the success probability of the TR-DSA. We first develop the closed-form expression for the success probability of a TR-DSA with the aid of multiple types of attacks, which is leveraged to develop the closed-form expression for the expected profit of a TR-DSA. The numerical analysis reveals that …
Lifelong Learning-Based Optimal Trajectory Tracking Control Of Constrained Nonlinear Affine Systems Using Deep Neural Networks, Irfan Ganie, Sarangapani Jagannathan
Lifelong Learning-Based Optimal Trajectory Tracking Control Of Constrained Nonlinear Affine Systems Using Deep Neural Networks, Irfan Ganie, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This article presents a novel lifelong integral reinforcement learning (LIRL)-based optimal trajectory tracking scheme using the multilayer (MNN) or deep neural network (Deep NN) for the uncertain nonlinear continuous-time (CT) affine systems subject to state constraints. A critic MNN, which approximates the value function, and a second NN identifier are together used to generate the optimal control policies. The weights of the critic MNN are tuned online using a novel singular value decomposition (SVD)-based method, which can be extended to MNN with the N-hidden layers. Moreover, an online lifelong learning (LL) scheme is incorporated with the critic MNN to mitigate …
A Hybrid Model-Based Data-Driven Framework For The Electromagnetic Near-Field Scanning, Yanming Zhang, Lijun Jiang
A Hybrid Model-Based Data-Driven Framework For The Electromagnetic Near-Field Scanning, Yanming Zhang, Lijun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
This article presents a novel hybrid approach for electromagnetic near-field scanning, combining model-based, i.e., Gaussian processes regression, and data-driven, i.e., dynamic mode decomposition, techniques. We first leverage the Latin hypercube sampling technique to achieve spatially sparse measurements. Subsequently, dynamic mode decomposition is applied to analyze the resulting spatiotemporal data with sparse spatial sampling, enabling the extraction of both frequency information and sparse dynamic modes. Finally, the Gaussian processes regression, also known as the Kriging method, is adopted for the full-state reconstruction. The proposed hybrid approach is benchmarked by an example of the crossed dipole antennas. The obtained results demonstrate that …
Impact Of Ai On The Hri Dynamic In Search And Rescue Operations Using Uav Swarms, Jordan Morrow, Maciej Jan Zawodniok, Anhar Sami Mohammed
Impact Of Ai On The Hri Dynamic In Search And Rescue Operations Using Uav Swarms, Jordan Morrow, Maciej Jan Zawodniok, Anhar Sami Mohammed
Electrical and Computer Engineering Faculty Research & Creative Works
Artificial intelligence (AI) offers significant benefits in search and rescue applications by enhancing the efficiency and effectiveness of the search. However, an over-reliance on AI can hinder the operation due to biases embedded in the underlying algorithms. This partiality, if left un-monitored, can pose a risk to the safety of those in need of disaster relief. Typically manifests into inaccuracies in the decision-making processes and if not carefully monitored can cause larger issues. This paper extends the knowledge presented in a previous work, which presents the design and modeling of search and rescue operations using unmanned aerial vehicle (UAV) swarms. …
Deep Learning For Uav Detection And Classification Via Radio Frequency Signal Analysis, Prajoy Podder, Maciej Zawodniok, Sanjay Madria
Deep Learning For Uav Detection And Classification Via Radio Frequency Signal Analysis, Prajoy Podder, Maciej Zawodniok, Sanjay Madria
Electrical and Computer Engineering Faculty Research & Creative Works
Unmanned Aerial Vehicles (UAVs) are advertised as great tool that benefits society and humanity. However, UAVs also pose significant security threats ranging from privacy invasions, to interfering with commercial aircraft landing and takeoff, to accidently crashing into vehicles or people, to military or terrorist attacks. Consequently, there is a pressing need to detect and identify UAVs to mitigate such potential risks. While image-based methods are crucial for UAV detection, radio frequency (RF) emissions offer additional valuable insights. Analyzing RF signals, such as those used in UAV-ground station communications, can provide information about UAV types based on distinct frequency usage or …
High-Sensitivity Fabry-Perot Interferometric Sensor Based On Microwave Photonics With Phase Demodulation, Ruimin Jie, Hongkun Zheng, Osamah Alsalman, Jie Huang, Chen Zhu
High-Sensitivity Fabry-Perot Interferometric Sensor Based On Microwave Photonics With Phase Demodulation, Ruimin Jie, Hongkun Zheng, Osamah Alsalman, Jie Huang, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
Optical fiber sensors have emerged as vital tools in various applications. Among them, Fabry-Perot interferometers (FPIs), have gained prominence due to their compactness and versatility in sensor design. Microwave photonics (MWP) techniques offer enhanced performance and flexibility for developing optical sensor interrogation methods. This paper proposes and experimentally demonstrates a novel MWP interrogation technique based on phase measurement for short-cavity FPI sensors. The technique utilizes the phase response of the FPI sensor within an MWP-assisted single radio frequency bandpass filter, providing improved sensitivity and dynamic sensing capabilities compared to traditional methods. Simulation and experimental results validate the effectiveness of the …
Online Continual Safe Reinforcement Learning-Based Optimal Control Of Mobile Robot Formations, Irfan Ganie, S. Jagannathan
Online Continual Safe Reinforcement Learning-Based Optimal Control Of Mobile Robot Formations, Irfan Ganie, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
In this work, a leader-follower tracking and formation control strategy for mobile robots (MRs) with uncertain dynamics is proposed. This strategy utilizes a continual lifelong safe reinforcement learning (CLSRL) framework based on multilayer neural networks (MNNs). The proposed design employs actor-critic MNNs, incorporating a barrier function. This function is derived from the Bellman optimality principle. It addresses the state constraints throughout the control design process. A novel online continual lifelong learning (CLL) method is introduced for MR formation. This method leverages the Bellman residual error for weight significance in MNNs. It addresses catastrophic forgetting and interlayer dependence through layer-specific regularizers. …
Lidar From The Sky: Uav Integration And Fusion Techniques For Advanced Traffic Monitoring, Baya Cherif, Hakim Ghazzai, Ahmad Alsharoa
Lidar From The Sky: Uav Integration And Fusion Techniques For Advanced Traffic Monitoring, Baya Cherif, Hakim Ghazzai, Ahmad Alsharoa
Electrical and Computer Engineering Faculty Research & Creative Works
Light detection and ranging (LiDAR) technology's expansion within the autonomous vehicles industry has rapidly motivated its application in numerous growing areas, such as smart cities, agriculture, and renewable energy. In this article, we propose an innovative approach for enhancing aerial traffic monitoring solutions through the application of LiDAR technology. The objective is to achieve precise and real-time object detection and tracking from aerial perspectives by integrating unmanned aerial vehicles with LiDAR sensors, thereby creating a potent Aerial LiDAR (A-LiD) solution for traffic monitoring. First, we develop a novel deep learning algorithm based on pointvoxel-region-based convolutional neural network (RCNN) to conduct …
Learning From The Past: Using Peer Data To Improve Course Recommendations In Personalized Education, Colton Walker, Sahra Sedigh Sarvestani, Ali R. Hurson
Learning From The Past: Using Peer Data To Improve Course Recommendations In Personalized Education, Colton Walker, Sahra Sedigh Sarvestani, Ali R. Hurson
Electrical and Computer Engineering Faculty Research & Creative Works
This research introduces a recommendation system designed to enhance student success by intelligently personalizing the semester schedules and graduation path based on the student's performance, interests, and background; and inspired by the academic journeys of similar students who have successfully graduated in the past. The proposed recommender system leverages a combination of Markov decision processes, Q-Learning, and collaborative filtering techniques to identify graduation paths with a higher likelihood of success for the student. The proposed model is versatile and generic and can be adapted to various disciplines if sufficient past historical data is available. The proposed model has been prototyped …
Highly Sensitive Liquid-Level Sensing Based On Microwave Frequency Domain Reflectometry And Interferometry, Chen Zhu, Osamah Alsalman, Jie Huang
Highly Sensitive Liquid-Level Sensing Based On Microwave Frequency Domain Reflectometry And Interferometry, Chen Zhu, Osamah Alsalman, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Frequency domain reflectometry (FDR) and interferometry are two widely used investigative techniques that have been instrumented using optical and microwave devices for a diverse array of sensing applications. In this paper, we present a highly sensitive liquid-level sensor using a custom hollow coaxial cable transmission line. Measurements of liquid levels with high sensitivity and resolution can be achieved by both FDR and interferometry-based measurements using the same sensor device. We show that FDR-based measurements are more straightforward for liquid-level sensing and are suitable for both small and large variations of liquid level, while interferometry-based measurements provide slightly higher measurement resolution …
A Method For Measuring The Transfer Function Inside A Compact Metallic Enclosure Using A Slot Antenna, Xiangrui Su, Wenchang Huang, Junghee Cho, Joonki Paek, Chulsoon Hwang
A Method For Measuring The Transfer Function Inside A Compact Metallic Enclosure Using A Slot Antenna, Xiangrui Su, Wenchang Huang, Junghee Cho, Joonki Paek, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
Radio frequency desensitization issues comprise two components: noise radiation sources and the transfer function from noise sources to the victim antenna. For modern electronic products, noise sources are often located inside a compact metal enclosure, making it difficult to measure the transfer function using conventional methods. Moreover, opening the metallic enclosure would dramatically change the transfer function, and inserting a near-field probe into the enclosure is challenging and may not even be possible because of the limited space inside. In this article, a novel practical method for measuring the transfer function inside a compact metallic enclosure is proposed and experimentally …
On The Feasibility Of A Direct Injection Probe With A Capacitively Coupled Return And Integrated Voltage Monitor, Aaron Harmon, Daniel Szanto, Victor Khilkevich, Daryl Beetner
On The Feasibility Of A Direct Injection Probe With A Capacitively Coupled Return And Integrated Voltage Monitor, Aaron Harmon, Daniel Szanto, Victor Khilkevich, Daryl Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
Characterizing the susceptibility of an IC while it is integrated within a system can be challenging. Characterization is even harder if one wants to know the waveform at the target IC pin when injecting a signal on the pin. In this work, the feasibility of a direct injection probe with a capacitively coupled return and integrated voltage monitor is proposed. This probe is advantageous because it does not need to be soldered to the test device and its ability to provide a measurement of the waveform on the target IC pin during the injection. Methods for reconstructing the pin waveform …
Evaluating Electromagnetic Interference Effects On Gnss Receivers, Giorgi Tsintsadze, Haran Manoharan, Arushi Sahai, Daryl G. Beetner, Brian Booth
Evaluating Electromagnetic Interference Effects On Gnss Receivers, Giorgi Tsintsadze, Haran Manoharan, Arushi Sahai, Daryl G. Beetner, Brian Booth
Electrical and Computer Engineering Faculty Research & Creative Works
Electromagnetic interference can be highly disruptive to global navigation satellite system (GNSS) receivers. Interference can be intentional but can also occur from electronics modules placed within the same system, where these modules may create sufficient unintended radiated emissions to disrupt GNSS operation. In this paper, GNSS receiver performance is evaluated in the presence of multi-tone interference. An expression for the GNSS correlator output in the presence of continuous wave interference (CWI) is derived and is extended to predict the carrier to noise density ratio, C/N0, of the receiver in the presence of multi-tone interference. C/N0 is widely used for characterizing …
Design Of Experiment Analysis On Multiple Pim Sources In An Rf Antenna System, Shengxuan Xia, Yuchu He, Haicheng Zhou, Hanfeng Wang, Chulsoon Hwang
Design Of Experiment Analysis On Multiple Pim Sources In An Rf Antenna System, Shengxuan Xia, Yuchu He, Haicheng Zhou, Hanfeng Wang, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
Passive intermodulation (PIM) has been identified as one of the common root causes for receiving sensitivity degradation (desense) on radiofrequency (RF) antennas working in frequency-division duplex mode. The component-level PIM characterization and simulation have been well-established over the years. However, the study has been using an ideal 50 Ω transmission line system while antenna modules are more complicated than a simple transmission line structure. Moreover, the metallic contacts can exist in multiple locations with different connection topologies in real applications. This paper provides a method to simulate the PIM performance caused by the metallic contacts in a practical environment. In …
Radiated Emission Modeling Of A Wireless Power Transfer System, Hanyu Zhang, Guanghua Li, Viswa Pilla, Chulsoon Hwang
Radiated Emission Modeling Of A Wireless Power Transfer System, Hanyu Zhang, Guanghua Li, Viswa Pilla, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
A radiated emission (RE) model of a wireless power transfer (WPT) system is proposed in this paper to help designers predict, analyze, and mitigate the RE issues during the design process. The proposed model employs both full-wave simulation and circuit simulation to derive a transfer function. Subsequently, it predicts the emission level by combining the transfer function with the measured transmitter waveform through a straightforward calculation. The predicted emissions match the measured RE peaks well up to 300 MHz, with the error within 3 dB. The impact of functional parameters, such as load and coil gap distance, is analyzed based …
A Model For Corona Streamer Propagation On Glass During An Air Discharge, Zhekun Peng, Jianchi Zhou, Darryl Kostka, David Pommerenke, Daryl G. Beetner
A Model For Corona Streamer Propagation On Glass During An Air Discharge, Zhekun Peng, Jianchi Zhou, Darryl Kostka, David Pommerenke, Daryl G. Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
Corona discharge to a glass surface is challenging to model due to a poorly understood air and surface ionization process. A modeling methodology based on the transmission line modeling (TLM) approach is proposed to simulate the streamer propagation process. The time-changing corona streamer resistance is estimated using the Rompe and Weizel spark model. The streamer is represented using small segments consisting of the arc resistance, per unit length (PUL) capacitance of the streamer, PUL inductance, a switch representing streamer formation, and a surface discharge gap voltage representing the voltage drop caused by ions within the streamer length. The propagation of …
Virtual Inertia Scheduling (Vis) For Microgrids With Static And Dynamic Security Constraints, Buxin She, Fangxing Li, Jinning Wang, Hantao Cui, Xiaofei Wang, Rui Bo
Virtual Inertia Scheduling (Vis) For Microgrids With Static And Dynamic Security Constraints, Buxin She, Fangxing Li, Jinning Wang, Hantao Cui, Xiaofei Wang, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
Microgrids feature a high penetration of inverter-interfaced distributed energy resources (DERs). The low inertia characteristic and fast dynamics of DERs pose challenges to conventional decoupled static economic operation and dynamic control design within microgrids. Hence, this paper proposed virtual inertia scheduling (VIS) for microgrids, aiming to ensure both economy and security. First, a unified framework for device-level control and grid-level operation is introduced, with VIS serving as a key application to address low inertia issues. VIS actively harnesses the controllability and flexibility of DERs to effectively manage microgrid inertia. It updates the conventional economic operation framework by incorporating the virtual …
Design Of The Tm010 Mode Cylindrical Cavity Resonator For Pcb Dielectric Characterization, Reza Asadi, Chaofeng Li, Seyedmehdi Mousavi, Seyed Moastafa Mousavi, Reza Vahdani, Xiaoning Ye, Donghyun Kim
Design Of The Tm010 Mode Cylindrical Cavity Resonator For Pcb Dielectric Characterization, Reza Asadi, Chaofeng Li, Seyedmehdi Mousavi, Seyed Moastafa Mousavi, Reza Vahdani, Xiaoning Ye, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents the study of the TM010 mode cylindrical resonator, which can be used for printed circuit board (PCB) material properties extraction, e.g., the dielectric constant (Dk) and the loss tangent (Df) extraction. The theoretical formulas of the resonance frequency and Q-factor of the resonator are presented. In real measurement, the TM010 mode cylindrical cavity resonator needs to be excited by the probe. The study emphasizes the impact of probe orientation, location, and field distribution on the accuracy of material property extraction. The relationship between cavity dimensions and resonance frequency is explored, highlighting the influence of cavity …
Novel Formulation For Generalization Of Mixed-Mode S-Parameters For Coupled Differential High-Speed Digital Channels, Manish K. Mathew, Kevin Cai, Chaofeng Li, Mehdi Mousavi, Shameem Ahmed, Donghyun Kim
Novel Formulation For Generalization Of Mixed-Mode S-Parameters For Coupled Differential High-Speed Digital Channels, Manish K. Mathew, Kevin Cai, Chaofeng Li, Mehdi Mousavi, Shameem Ahmed, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
As the demand for higher data rates intensifies, achieving accurate S-parameter calculation becomes increasingly critical. The conventional single-ended to mixed-mode S-parameter conversion formulation assumes uncoupled structures, which may not be true for high-speed digital channels. This work introduces a novel, generalized formulation for mixed-mode S-parameters and their corresponding transformation matrices [M1] and [M2], enabling comprehensive analysis of multi-pair coupled differential traces. An intra-pair crosstalk analysis of a tightly coupled strip line and microstrip line verifies and highlights the difference between the proposed and old formulations. A loosely coupled case is analyzed as an additional validation of the proposed formulation. Finally, …
A Tensor-Based Data-Driven Approach For Multidimensional Harmonic Retrieval And Its Application For Mimo Channel Sounding., Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Ping Yuan, Lijun Jiang, Steven Gao
A Tensor-Based Data-Driven Approach For Multidimensional Harmonic Retrieval And Its Application For Mimo Channel Sounding., Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Ping Yuan, Lijun Jiang, Steven Gao
Electrical and Computer Engineering Faculty Research & Creative Works
In wireless channel sounding, accurately estimating multiple parameters within a multipath signal, such as azimuth, elevation, Doppler shift, and delay, necessitates addressing the challenges posed by the multidimensional harmonic retrieval (MHR) problem. To overcome these complexities, we propose a framework based on high-order dynamic mode decomposition (HODMD) that designed for robustly estimating frequencies of interest from high-dimensional sinusoidal signals, particularly in additive white Gaussian noise conditions. The HODMD approach, a hybrid algorithm amalgamating high-order singular value decomposition (HOSVD) and dynamic mode decomposition (DMD), operates by initially decomposing observed tensorial data into a core tensor and R mode matrices through HOSVD. …
Behavior Model Of A Multiphase Voltage Regulator Module With Rapid Voltage Drop Protection, Junho Joo, Hanyu Zhang, Hanfeng Wang, Wei Shen, Zhigang Liang, Lihui Cao, Seungtaek Jeong, Chulsoon Hwang
Behavior Model Of A Multiphase Voltage Regulator Module With Rapid Voltage Drop Protection, Junho Joo, Hanyu Zhang, Hanfeng Wang, Wei Shen, Zhigang Liang, Lihui Cao, Seungtaek Jeong, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a modeling method of voltage regulator module (VRM) with rapid voltage drop protection is introduced. The proposed VRM model captures a pulse-width modulation scheme developed to counteract substantial load currents with high di/dt, resulting in a large voltage drop across the power delivery network (PDN). The equations to describe the non-linear behavior associated with the multiphase VRM behavior are proposed and successfully validated for both light and heavy loads, the latter being particularly crucial to trigger the voltage drop protection measures.
Modeling Of Power Distrubition Network (Pdn) Noise Coupling Induced Clock Phase Noise, Zhekun Peng, Junyong Park, Chaofeng Li, Joey Stecher, Srinivas Venkataraman, Xu Wang, Granthana Rangaswamy, Donghyun Kim
Modeling Of Power Distrubition Network (Pdn) Noise Coupling Induced Clock Phase Noise, Zhekun Peng, Junyong Park, Chaofeng Li, Joey Stecher, Srinivas Venkataraman, Xu Wang, Granthana Rangaswamy, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
Phase noise analysis is important to clock design. Noise sources of spurs shown on the phase noise result are challenging to find out due to the unknown source locations and coupling mechanisms. Noise from power distribution network (PDN) is one of the most troublesome sources. A behavioral modeling methodology is proposed to simulate the clock phase noise induced by PDN noise coupling for two different mechanisms: PDN-to-clock additive coupling and PDN-to-PDN up-conversion modulation. The thermal noise and 1/f flicker noise are simplified to provide a straightforward view of spur level. The model can be applied to both single-ended clock and …
Lifelong Direct Error-Driven Learning For Uav Altitude Estimation In Different Weather Conditions, Shirin Nasr-Esfahani, Jagannathan Sarangapani
Lifelong Direct Error-Driven Learning For Uav Altitude Estimation In Different Weather Conditions, Shirin Nasr-Esfahani, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
While deep neural networks achieve remarkable visual perception capabilities for UAV position and orientation estimation, their resilience to different weather conditions still needs improvement. These models often suffer from catastrophic forgetting when adapted to new environments, losing previously acquired knowledge. Lifelong learning methods aim to balance learning flexibility and memory stability. In this paper, we present an image-based approach to estimate the relative altitude of a UAV using 2D images under varying weather conditions, including sunny, sunset, and foggy scenarios. Our experiments demonstrate significant performance degradation when the model is trained sequentially on different weather datasets, especially when new images …
Cascading Of 2d And 3d Simulations Of Asic Substrate Interconnect Up To 100 Ghz, Zhekun Peng, Junyong Park, Sathvika Bandi, Santosh Pappu, Srinivas Venkataraman, Xu Wang, Granthana Ranzaswamy, Donghyun Kim
Cascading Of 2d And 3d Simulations Of Asic Substrate Interconnect Up To 100 Ghz, Zhekun Peng, Junyong Park, Sathvika Bandi, Santosh Pappu, Srinivas Venkataraman, Xu Wang, Granthana Ranzaswamy, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
A method of cascading 3D models and 2D models to model the full channel of ASIC package substrate interconnects is proposed, showing good match to full-wave results in S-parameter and TDR up to 100 GHz.
Impact Of Non-Functional Pads Location On Eye Diagram Performance, Mehdi Mousavi, Kevin Cai, Junyong Park, Chaofeng Li, Manish K. Mathew, Reza Asadi, Shameem Ahmed, Donghyun Kim, Bidyut Sen
Impact Of Non-Functional Pads Location On Eye Diagram Performance, Mehdi Mousavi, Kevin Cai, Junyong Park, Chaofeng Li, Manish K. Mathew, Reza Asadi, Shameem Ahmed, Donghyun Kim, Bidyut Sen
Electrical and Computer Engineering Faculty Research & Creative Works
This study shows that placing four NFPs in selective PCB layers significantly improves signal integrity, reducing minimum jitter from 18.28 ps to 12.81 ps and maximum jitter from 27.66 ps to 22.03 ps.
Lifelong Safe Optimal Adaptive Tracking Control Of Nonlinear Strict-Feedback Discrete-Time Systems, Behzad Farzanegan, S. Jagannathan
Lifelong Safe Optimal Adaptive Tracking Control Of Nonlinear Strict-Feedback Discrete-Time Systems, Behzad Farzanegan, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a comprehensive approach for achieving multi-task safe optimal adaptive tracking (MSOAT) for a class of nonlinear discrete-time systems, particularly those in strict-feedback form, utilizing a multi-layer neural network (MNN)-based framework. To begin, a cost function with a novel Barrier function (BF) term is introduced for each subsystem to address the weak safely reachable problem, serving as a crucial tool for guiding the system's trajectory toward the safe set while avoiding unwanted sets. To deal with the tracking problem, the Hamilton-Jacobi-Bellman (HJB) framework is used through the actor-critic MNN-based backstepping technique to estimate the solution of the value …
Suppression Of Power Distribution Network Pcb-Package Resonance For Low Target Impedance, Francesco De Paulis, Faye Squires, Yifan Ding, Matteo Cocchini, Matthew Doyle, Samuel Connor, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang
Suppression Of Power Distribution Network Pcb-Package Resonance For Low Target Impedance, Francesco De Paulis, Faye Squires, Yifan Ding, Matteo Cocchini, Matthew Doyle, Samuel Connor, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
The suppression of the large resonance peak that may appear due to the equivalent parallel circuit between the package capacitance and PCB inductance is discussed. Such resonance may be amplified if the decoupling capacitors are not appropriately selected. The relevant parameters involved in the PDN design, and a feasible solution strategy are presented based on the identification of a simplified equivalent circuit that is able to replicate the resonant behavior. The optimization of the relevant parameters of such circuit are able to suggest the best strategy for identifying the decoupling capacitors with appropriate values of parasitic inductance and resistance.
Ai Trustworthy: Ethical Challenges And Strategies, Jian Liu, Iwan Sandjaja, Donald C. Wunsch
Ai Trustworthy: Ethical Challenges And Strategies, Jian Liu, Iwan Sandjaja, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
This paper explores the pivotal role of trust in the widespread application of Artificial Intelligence (AI) across various domains. We review AI applications in sectors like energy, healthcare, and autonomous vehicles and discuss the crisis of human trust they face. This paper introduces a novel framework that delineates the relationship between AI transparency and user trust, highlighting specific industry applications. Through a systematic review of recent literature, we first delve into factors such as emotional response, acceptance, transparency, accuracy, and interpretability that shape human trust in AI. We then underscore the necessity of ethical AI practices and highlight the importance …
Understanding Student Perceptions Of Project Impact In The Epics In Ieee Service-Learning Program, Stephanie Gillespie, Steve Eugene Watkins, Ashley F. Moran
Understanding Student Perceptions Of Project Impact In The Epics In Ieee Service-Learning Program, Stephanie Gillespie, Steve Eugene Watkins, Ashley F. Moran
Electrical and Computer Engineering Faculty Research & Creative Works
This innovative practice full paper addresses the assessment component of student service-learning projects. Through IEEE, the Engineering Projects in Community Service in IEEE committee (EPICS in IEEE) sponsors service-learning projects for student groups in project areas spanning human services, environmental, access and abilities, and education and outreach. Service learning and community-engaged learning can provide positive outcomes for both the students and the community organization or community members. The intent of assessment in a service-learning project or program is that both the student-learning outcomes and the humanitarian/community impact of the implementation or engagement are gauged. Often, the latter aspect of assessment …