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2024 International Conference on Advanced Mechatronic Systems, ICAMechS 2024

作者： An, Zizhen Deng, Mingcong Tokyo University of Agriculture and Technology Graduate School of Engineering Department of Electrical Engineering and Computer Science Tokyo Japan

ISBN: (纸本)9798350366204

In this note, a new structure of Right Coprime Factorization (RCF) for nonlinear systems with uncertainty has been proposed based on a time-varying Bezout identity. This is inspired from the concept of dilation from homogeneous theory. However, this time-varying dilation in right coprime factorized uncertain nonlinear systems is not limited to homogeneous plants but is integrated into Bezout identity so as to ensure the bounded input bounded output (BIBO) stability of uncertain systems. Additionally, simulation results of two numerical examples are exhibited to validate the proposition. © 2024 IEEE.

关键词： Nonlinear simulations

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Spectral Learning of Shared Dynamics Between Generalized-Linear Processes 38

Spectral Learning of Shared Dynamics Between Generalized-Lin...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Oganesian, Lucine L. Sani, Omid G. Shanechi, Maryam M. Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA United States Ming Hsieh Department of Electrical and Computer Engineering Thomas Lord Department of Computer Science Alfred E. Mann Department of Biomedical Engineering Neuroscience Graduate Program University of Southern California Los AngelesCA United States

Generalized-linear dynamical models (GLDMs) remain a widely-used framework within neuroscience for modeling time-series data, such as neural spiking activity or categorical decision outcomes. Whereas the standard usage of GLDMs is to model a single data source, certain applications require jointly modeling two generalized-linear time-series sources while also dissociating their shared and private dynamics. Most existing GLDM variants and their associated learning algorithms do not support this capability. Here we address this challenge by developing a multi-step analytical subspace identification algorithm for learning a GLDM that explicitly models shared vs. private dynamics within two generalized-linear time-series. In simulations, we demonstrate our algorithm's ability to dissociate and model the dynamics within two time-series sources while being agnostic to their respective observation distributions. In neural data, we consider two specific applications of our algorithm for modeling discrete population spiking activity with respect to a secondary time-series. In both synthetic and real data, GLDMs learned with our algorithm more accurately decoded one time-series from the other using lower-dimensional latent states, as compared to models identified using existing GLDM learning algorithms. © 2024 Neural information processing systems foundation. All rights reserved.

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Sensitivity Analysis for Neutral Reactor Optimization 8

Sensitivity Analysis for Neutral Reactor Optimization

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8th Workshop on Communication Networks and Power Systems, WCNPS 2023

作者： Balbino, L.S. Dantas, K.M. Neves, W.L.A. Electrical Engineering Graduate Program Campina Grande Brazil Department of Electrical Engineering PB Campina Grande Brazil

ISBN: (纸本)9798350343571

This paper presents an approach for choosing neutral reactors in transmission lines (TL) with shunt compensation. Data from the Brazilian Power Grid were used for digital simulations with ATPDraw, and a sensitivity analysis was carried out with various parameters (line length, neutral reactor, fault location) to find curves that correlate the optimum reactor value with the transmission line shunt compensation level. The influence of line length and compensation level are discussed. Limitations are presented, and the results show that the approach allows reactors to be obtained efficiently for most of the compensation range. © 2023 IEEE.

关键词： Electric lines

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Modeling of Electrostatics and Currents in a Forward-Biased p-n Junction

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IEEE Transactions on Electron Devices 2024年第8期71卷 4489-4497页

作者： Lin, Kuan-Wun Taur, Yuan National Taiwan University Graduate Institute of Electronics Engineering Taipei10617 Taiwan University of California San Diego Department of Electrical and Computer Engineering La Jolla CA92093 United States

A general model is developed for forward-biased p-n junctions with arbitrary doping concentrations biased at any injection level. It goes beyond the commonly practiced depletion approximation, which is valid only under the low-level injection condition. It is shown that when the applied junction voltage exceeds the built-in potential, the profile of net charge density shrinks to two antisymmetric spikes, one going positive and one going negative, with the same magnitude given by the average of the n-type and p-type doping concentrations. It is also shown that under high-level injection condition, the drift current components become dominant, in some cases yielding an exp(qV/kT) dependence of the total current instead of the commonly perceived exp(qV/2kT) dependence (here, V is the intrinsic junction voltage). By equating the sum of drift and diffusion current densities on both sides of the junction, analytical expressions are derived for the electric fields and, therefore, the total currents. Finally, the decay lengths of excess carriers in the quasi-neutral regions are solved numerically from the current continuity equations coupled to Poisson's equation with no assumptions of charge neutrality. It is shown that the decay lengths in the high-level injection regime are doping-dependent and are longer than the well-known minority-carrier diffusion lengths in the low-level injection regime. © 1963-2012 IEEE.

关键词： Electric fields

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MPEG-DASH Multi-View Video and Audio Transmission QoE Over HTTP/2 Stream

MPEG-DASH Multi-View Video and Audio Transmission QoE Over H...

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2024 International Conference on Advanced Technologies for Communications, ATC 2024

作者： Wakayama, Yamato Nunome, Toshiro Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350353983

In this paper, we consider multi-view video and audio streaming using MPEG-DASH, which enables to transmit video tailored to the network conditions over HTTP communication. This paper uses HTTP/2 instead of HTTP/1.1, which the authors previously used. HTTP/2 manages a series of request-response exchanges called a stream, which is assigned a unique stream ID. We perform a subjective experiment under various network conditions to evaluate application-level QoS and QoE. From the evaluation results, we investigate the effect of the HTTP/2 stream on the video and audio quality of the users in the multi-view video transmission scenario. © 2024 IEEE.

关键词： Audio streaming

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QoE Comparison between Multi-User OFDMA and Reliable Groupcast for Wireless LAN Audiovisual Transmission

QoE Comparison between Multi-User OFDMA and Reliable Groupca...

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Deguchi, Daiki Nunome, Toshiro Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350364866

This paper compares video and audio QoE of OFDMA multi-user transmission and reliable groupcast over wireless LAN. We assume video and audio transmission to several terminals simultaneously. As a reliable groupcast method, we employ Unsolicited Retry, a technique of IEEE 802.11aa GroupCast with Retries. We utilize IEEE 802.11ax for OFDMA transmission. We evaluate application-level QoS by computer simulation. We then assess QoE through a subjective experiment with video and audio streams generated by the output timing obtained from the simulation. We notice that each method has a situation to be applied appropriately. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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Barrier Function-Based Backstepping Fractional-Order Sliding Mode Control for Quad-Rotor Unmanned Aerial Vehicle under External Disturbances

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IEEE Transactions on Aerospace and Electronic Systems 2024年第1期60卷 716-728页

作者： Liu, Bowen Wang, Yingxun Mofid, Omid Mobayen, Saleh Khooban, Mohammad Hassan Beihang University School of Automation Science and Electrical Engineering Beijing100191 China University of Zanjan Department of Electrical Engineering Zanjan45371-38791 Iran National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliou64002 Taiwan Aarhus University Department of Electrical and Computer Engineering Aarhus8200 Denmark

The main control objective for the quad-rotor system is the attitude and position tracking control which is accomplished in this article using the backstepping fractional-order sliding mode control approach combined with the adaptive tuning based barrier function theory. The quad-rotor's dynamical model is obtained at the appearance of the disturbance that is entered to the quad-rotor system by an exterior force. Hence, the attitude and position tracking errors between the quad-rotor's actual states and their desired trajectory are defined. Afterward, the fractional-order sliding surfaces are defined to guarantee finite-time reachability of the defined tracking error. The designed fractional-order surface eases the control process due to the removal of the high-derivative of virtual controllers. Then, the extended adaptive barrier function laws named fractional-order-based adaptive barrier function laws are employed to eliminate the knowledge of the upper bounds of external disturbances. The Lyapunov theory concept mixed with the backstepping control strategy is used to demonstrate that the fractional-order sliding surface reaches the neighborhood of origin in the finite time. Finally, simulation results in various scenarios on the MATLAB/ Simulink environment are provided to show that the designed control procedure in this article is an efficient control technique to assure that attitude and position's trajectories of the quad-rotor system track desired trajectories properly in the existence of the external disturbances. Moreover, the designed method is compared to the existing method to validate the efficiency of the proposed method. Lastly, experimental results using the Speedgoat real-time target machine is implemented to assure validity of the recommended method. © 1965-2011 IEEE.

关键词： Backstepping

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A 25.1-TOPS/W Sparsity-Aware Hybrid CNN-GCN Deep Learning SoC for Mobile Augmented Reality

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IEEE Journal of Solid-State Circuits 2024年第11期59卷 3840-3852页

作者： Huang, Wen-Cong Lin, I-Ting Lin, Ying-Sheng Chen, Wen-Ching Lin, Liang-Yi Chang, Nian-Shyang Lin, Chun-Pin Chen, Chi-Shi Yang, Chia-Hsiang National Taiwan University Graduate Institute of Electronics Engineering Taipei106216 Taiwan MediaTek Hsinchu300096 Taiwan University of California at Berkeley Department of Electrical Engineering and Computer Sciences BerkeleyCA94720 United States Taiwan Semiconductor Research Institute Hsinchu300091 Taiwan Graduate Institute of Electronics Engineering National Taiwan University Department of Electrical Engineering Taipei106216 Taiwan

Augmented reality (AR) has been applied to various mobile applications. Modern AR algorithms include neural networks, such as convolutional neural networks (CNNs) and graph convolutional networks (GCNs). The high computational complexity of these networks poses challenges for real-time operation on energy-constrained devices. This article presents the first energy-efficient hybrid CNN-GCN system-on-chip (SoC) for mobile AR. A CNN engine exploits the channel-wise structured feature sparsity to eliminate redundant computations and data movements. By utilizing the proposed channel-sparse encoding scheme on a specialized processing element (PE) architecture, up to 8× higher throughput and × higher energy efficiency can be achieved. A reconfigurable convolution PE (CPE) array is deployed for efficient CNN inference. A GCN engine is designed to implement skeleton-based action recognition and gesture recognition. Up to 71% of total operations and 39% of memory footprint can be reduced by leveraging the data and graph properties. A RISC-V MCU is integrated for system control and network deployment. The proposed SoC is implemented in a 28-nm CMOS technology with a core area of 8.28 mm2. By exploiting various sparsity levels across network layers, the chip achieves an up to 3.277-TOPS peak performance and a 25.1-TOPS/W energy efficiency for sparse CNN inference, 2.0× higher energy-efficient than prior arts. It also achieves an up to 72 actions/s recognition throughput, 18× faster than the state of the art. © 2024 IEEE.

关键词： Engines

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A 60-GHz Phase-Locked Loop Using Standing- Wave Oscillator for Clock Distribution in 2-D Phased-Array

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IEEE Microwave and Wireless Technology Letters 2024年第6期34卷 679-682页

作者： You, Ying-Han Chen, Sih-Ying Lin, Pin-Yu Chien, Jun-Chau National Taiwan University Graduate Institute of Electronics Engineering Taipei10617 Taiwan University of California at Berkeley Department of Electrical Engineering and Computer Sciences BerkeleyCA94720 United States

This letter presents a 60-GHz analog phase-locked loop (PLL) incorporating a half-wavelength standing-wave oscillator (SWO) as part of the clock distribution network in a sub-THz 2-D phased-array transceiver. The frequency is selected as one-fourth of the target carrier frequency to comply with the 625-μ m half- wavelength element spacing requirement while facilitating array scaling. The PLL features a sampler-based phase detector (PD) and retiming flip-flop at the divider chain output to ensure minimal noise injection. Fabricated in TSMC 28-nm CMOS, the measurement results show an integrated jitter of 87.5 fsec from 1 kHz to 100 MHz. Consuming 31.35 mW of power, the presented PLL achieves a figure-of-merit of -270 dB. © 2023 IEEE.

关键词： Phase locked loops

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RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

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2024 Prognostics and System Health Management Conference, PHM 2024

作者： Cai, Congrui Lu, Zhonghai School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Embedded Systems Master Program Sweden School of Electrical Engineering and Computer Science Department of Electrical Engineering KTH Royal Institute of Technology Sweden

ISBN: (纸本)9798350360585

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms. © 2024 IEEE.

关键词： Long short-term memory

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