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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Johnny, Milad Valaee, Shahrokh University of Toronto Electrical and Computer Engineering Department Toronto Canada

ISBN: (纸本)9798331517786

This paper proposes an indoor localization strategy that utilizes fixed reflector points. The strategy assumes the presence of a base station (BS) with a known location, equipped with Angle of Arrival (AoA) and Time of Arrival (ToA) measurement capabilities. The localization process comprises two stages. In the initial stage, a systematic environmental scan identifies reflector points, facilitating the creation of a detailed map of their locations. Next, to achieve precise localization, a maximization problem is formulated. For each candidate location, the method assesses the likelihood of a set of measurements to the reflectors map. This approach accelerates user localization compared to fingerprint search algorithms. Simulation results provide compelling evidence for the effectiveness of this strategy in speeding up data gathering in the localization procedure. © 2024 IEEE.

关键词： Indoor positioning systems

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Overall Performance Improvement of Radiation-Hardened SRAM Cells through Assist Techniques 12

Overall Performance Improvement of Radiation-Hardened SRAM C...

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12th International Conference on Internet of Everything, Microwave, Embedded, Communication and Networks, IEMECON 2024

作者： Patil, Akshat Raj Vattoly, Abin Rathore, Nitesh Kumar Singh, Pooran Department of Electrical and Computer Engineering Mahindra University Hyderabad India

ISBN: (纸本)9798350387315

The harsh environment in space is characterized by high-energy particles and extreme temperature swings, which can cause single event upsets (SEUs) in conventional 6T SRAM cells. These cells are not resistant to SEUs and have a low critical charge (Qc), making them unsuitable for use in space applications. Radiation-hardened SRAM (RHSRAM) cells are an alternative to conventional SRAM cells, as they are resistant to SEUs and can recover from soft errors on their own. Researchers have proposed many different RHSRAM cells over the years, including the RHBD 10T, RHMD 10T, SRRD 12T, and RHPD 12T cells. This paper presents a simulation and estimation of the design metrics of these four RHSRAM cells. The results show that the SRRD 12T cell has the best overall performance, with the highest EQM (error-free memory) value. Finally, the paper proposes read/write assist techniques to improve the read/write design metrics of the RHSRAM cells. These techniques are shown to further improve the overall EQM value of the SRRD 12T cell. © 2024 IEEE.

关键词： Radiation hardening

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A New Initialization Method for K-means Clustering 20

A New Initialization Method for K-means Clustering

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20th CSI International Symposium on Artificial Intelligence and Signal Processing, AISP 2024

作者： Baratalipour, Elahe Kabudian, Seyed Jahanshah Fathi, Zahra Razi University Department of Electrical and Computer Engineering Kermanshah Iran

ISBN: (纸本)9798350383942

Clustering techniques are widely used for data analysis and knowledge discovery in various fields. Among them, the K-means algorithm is a popular and efficient method for categorization of data into clusters based on similarity. However, the effectiveness of the K-means algorithm heavily depends on the initial selection of cluster centroids. In traditional K-means, the initial centroids are randomly chosen from the input data. This random initialization can lead to suboptimal clustering results, as the algorithm is sensitive to the initial configuration. The resulting clusters may not accurately represent the underlying structure of the data and may vary for different runs of the algorithm. In the proposed improved K-means for the initial centroids, we first find the largest and smallest value based on top-two important features of the data set and perform clustering in this space. Then we take the data close to the average of each cluster as the center of that cluster. The experimental results on three well-known datasets, TIMIT, Iris and Immunotherapy shows that the proposed initialization method outperforms other ones in terms of clustering validity and accuracy measures. © 2024 IEEE.

关键词： K-means clustering

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Exploring Noise- Resilient Spiking Neural Encoding using ∑†∑ Neurons 67

Exploring Noise- Resilient Spiking Neural Encoding using ∑...

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67th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2024

作者： Sreekumar, R. Mullick, Faiyaz E. Morshed, Md Golam Ghosh, Avik W. Stan, Mircea R. University of Virginia Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350387179

Researchers are increasingly focusing on spiking neurons to enhance the energy efficiency of edge machine learning (ML) models. Spiking neural encoding has evolved from traditional methods like Integrate and Fire and Time to First Spike to techniques such as Delta and Sigma-delta modulation (SD), enabling sparser and energy-efficient feature representation. In this work, we introduce the Sigma-Delta-Sigma (∑†∑/SDS) neuron, a noise-invariant spiking neural encoding technique. Our aim with this neural encoding is to emulate the robustness of a specific class of biological neurons to input noise by effectively filtering out noise-like features from the input stimuli. While noise injection in training prevents overfitting, improper noise profiles can be detrimental to the inference accuracy of a model. Our objective with the SDS encoding is to develop noise-resilient spiking neural network models capable of being trained with ideal features, while still being able to extract features from low-quality data during the inference phase. To assess the robustness of our technique, we implement an information encoding ensemble model that demonstrates a 6.2x improvement in robustness when the Signal-to-Noise Ratio (SNR) of the incoming signal is 1 dB. Furthermore, we evaluate the performance of the SDS neurons in more complex models such as a Liquid State Machine (LSM), where the model exhibits a 3.87% improvement in the predictive accuracy against the baseline model when tested against input features with SNR degradation from 55 to 1 dB. © 2024 IEEE.

关键词： Energy efficiency

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Plasmonic Au Decorated CdS Nanowire Arrays for Enhanced Photoelectrochemical Hydrogen Evolution

Plasmonic Au Decorated CdS Nanowire Arrays for Enhanced Phot...

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2024 Photonics North, PN 2024

作者： Alam, Kazi M. Chaulagain, Narendra Manuel, Ajay P. Shankar, Karthik Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

ISBN: (纸本)9798350366365

In this work, an exciton-plasmon coupled system comprising hexagonal CdS nanowire and Au nanoparticle has been synthesized, characterized and tested in photoelectrochemical (PEC) water-splitting experiment. The significantly improved device performance of the Au@CdS hybrid in comparison to that of bare CdS nanowires has been primarily attributed to plasmon-induced hot electron injection from Au nanoparticles into adjacent CdS nanowires. © 2024 IEEE.

关键词： Nanowires

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Design of a Polyvalent Test Platform for Evaluation of Self-Sustained Oscillation in Multi-chip Power Modules

Design of a Polyvalent Test Platform for Evaluation of Self-...

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2025 IEEE International Workshop on Integrated Power Packaging, IWIPP 2025

作者： Boutry, Arthur Lemmon, Andrew N. The University of Alabama Department of Electrical and Computer Engineering Tuscaloosa United States

This study introduces a polyvalent test platform to investigate self-sustained oscillation (SSO) in parallel-connected Silicon Carbide (SiC) MOSFETs. Examining the oscillatory behavior associated with SiC multi-chip modules, this work uses an LTspice simulation framework and presents an analysis of parameters influencing SSOs. The study employs a Monte Carlo simulation to explore various circuit configurations and their susceptibility to SSO, offering insights into parameter importance. © 2025 IEEE.

关键词： Silicon carbide

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Overvoltage Mitigation Filter Using High-Frequency Cable Modeling in Long Transmission Lines for Silicon Carbide Inverter Systems 14

Overvoltage Mitigation Filter Using High-Frequency Cable Mod...

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14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Lee, Yun-Jin Lee, Kyo-Beum Ajou University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798331516116

This paper analyzes a design of overvoltage mitigation filter using high-frequency cable modeling in long transmission lines for silicon carbide inverter systems. The SiC inverter systems operating with long transmission lines may experience overvoltage caused by voltage reflection, leading to insulation breakdown. The proposed method to address the problem of overvoltage occurring on long transmission lines involves connecting a RLC filter at the end of the cable to reduce the overvoltage. The RLC filter is calculated by deriving the characteristic impedance using the parameters of the cable modeling. The validity of cable modeling and designing overvoltage mitigation filter is verified through simulation results. © 2025 IEEE.

关键词： Silicon carbide

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Photonic Band engineering for Surface Emitting Ultraviolet Lasers

Photonic Band Engineering for Surface Emitting Ultraviolet L...

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2024 Photonics North, PN 2024

作者： Vafadar, Mohammad Fazel Zhao, Songrui Department of Electrical and Computer Engineering McGill University Montreal Canada

ISBN: (纸本)9798350366365

关键词： Gallium nitride

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Inverse Reticle Optimization with Quantum Annealing and Hybrid Solvers

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IEEE Access 2024年 12卷 33069-33078页

作者： Fang, Po-Hsun Chen, Yan-Syun Wu, Jhih-Sheng Yu, Peichen National Yang Ming Chiao Tung University College of Electrical and Computer Engineering Department of Photonics Hsinchu30010 Taiwan

Reticle optimization is a computationally demanding task in optical microlithography for advanced semiconductor fabrication. In this study, we explore the effectiveness of D-Wave's quantum annealing (QA) and hybrid steepest descent (SD) solvers in solving pixelated binary reticle optimization problems. We show that the energy derived from the objective function depends on annealing time and inter-sample correlation. Specifically, longer annealing times and reduced inter-sample correlations result in lower energy. Moreover, introducing efficient pausing strategies in forward annealing could reduce the QA runtime by approximately 100-fold while achieving similar results to long annealing times. Finally, reticles with increased variables lead to widespread irregular values in default sorted QA energies due to quantum chain breakages, which could potentially limit the probability of attaining the optimal solution. A hybrid approach that applies the classical SD algorithm to the QA results increases the probability of locating the global minimum solution and reduces runtime to about one-third compared to the classical SD solver. These findings facilitate our comprehension of quantum computing for accelerating computational lithography in semiconductor manufacturing. © 2013 IEEE.

关键词： Linear programming

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ML-Assisted Sub-synchronous Oscillation Detection and Localization in Type-4 Wind Farms under Weak Grid Conditions 50

ML-Assisted Sub-synchronous Oscillation Detection and Locali...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Abu-Rub, Omar Umar, Muhammad F. Sheikh Ali, Jana A. Qiblawey, Yazan Alassi, Abdulrahman Saaedfard, Maryam Shadmand, Mohammad B. Department of Electrical & Computer Engineering Georgia Tech Atlanta United States Department of Electrical and Computer Engineering Texas A&M University at Qatar Doha Qatar Department of Electrical Engineering Qatar University Doha Qatar Iberdrola Innovation Middle East Doha Qatar Department of Electrical & Computer Engineering University of Illinois Chicago Chicago United States

ISBN: (纸本)9781665464543

Recently, incidents of the sub-synchronous oscillation (SSO) occurrence have significantly increased in the power system integrated with renewable energy resources. In the current power system, as more distributed renewable energy resources replace conventional synchronous generator-based sources, the grid is transformed into a low-inertia power system. The low inertia and distributed nature of renewable energy systems contribute to weak grid conditions. In the type-4 wind turbine generators (WTG) SSO can originate due to the interaction of fast dynamics of power converter’s control and weak AC grid. If SSO is not detected and mitigated in a timely manner, it can cause severe damage to the WTG’s shaft, turbine structure, and can pose severe type of instability in the power system that may lead to cascaded tripping. Therefore, this paper presents a machine learning (ML) based scheme for fast and accurate detection of SSO and localizing the WTG’s control parameter that triggers SSO under the influence of weak AC grid. The proposed SSO detection and localization scheme features a dual neural network structure (DNNS) based on long short-term memory (LSTM). The first NN structure detects SSO and triggers second NN structure when SSO is detected. The second multiclass NN identifies the control parameter of WTG that triggered this SSO and provides a recommendation/ reference for the SSO mitigation scheme. The effectiveness of the proposed ML based SSO detection and localization scheme is verified via confusion matrix and simulation that analyzes different cases related to the ML scheme validation. © 2024 IEEE.

关键词： Long short-term memory

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