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An LMI adaptive-barrier function global sliding mode control of uncertain nonlinear systems with input saturation

Ain Shams engineering Journal 2024年第2期15卷

作者： Rahimpour, Rahim Sepestanaki, Mohammadreza Askari Mobayen, Saleh Mokhtare, Zahra Fekih, Afef Assawinchaichote, Wudhichai Zhilenkov, Anton Electrical Engineering Department University of Zanjan Zanjan Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou640301 Taiwan Department of Electrical and Computer Engineering University of Louisiana at Lafayette Lafayette United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok10140 Thailand Department of Cyber-Physical Systems St. Petersburg State Marine Technical University Saint-Petersburg190121 Russia

This paper proposes a barrier function-based adaptive control strategy with a nonlinear sliding surface for a class of uncertain dynamic systems with input saturation. Its main objectives are to ensure robustness to parametric and non-parametric uncertainties whilst eliminating the reaching phase. A global nonlinear switching surface is defined and an adaptive barrier function sliding mode control approach is derived. The barrier strategy is adopted to ensure the convergence of the states to the desired values without overestimating the control gains. System stability is analyzed using the Lyapunov stability theory. The control parameters are obtained using the linear matrix inequality (LMI) approach. The control law is designed to remove the reaching phase. The effectiveness of the proposed approach was validated using a simulation study. The proposed control approach can easily be implemented to various nonlinear uncertain systems. © 2023 THE AUTHORS

关键词： Linear matrix inequalities

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Artificial Intelligence Scoring Algorithm for English Translation Based on DNN

Artificial Intelligence Scoring Algorithm for English Transl...

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International Conference on Smart Technologies For Smart Nation (SmartTechCon)

作者： R Krishna Priya Sabarmathi K R Aanandha Saravanan K Niranjanamurthy M Aashish A. Gadgil Azarudeen K Department of Engineering-Electrical Section College of Engineering and Technology University of Technology and Applied Sciences Shinas Sultanate of Oman Department of Information Technology Bannari Amman Institute of Technology Sathyamangalam Tamilnadu India Department of ECE Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of AI ML BMS Institute of Technology and Management Bangalore Karnataka India Department of ECE KLS GOGTE Institute of Technology Belagavi Karnataka India Department of Computer Science and Engineering Velammal College of Engineering and Technology Madurai India

With the popularity of languages and the increasing demand for language translation, the optimization of artificial intelligence scoring algorithm for English translation has become the urgent need of the translation market. Based on the deep neural network(DNN) algorithm, it continuously integrates modern technology to realize information collection, storage, analysis and application, which promotes the deep integration of the DNN algorithm in the field of intelligent identification and expands the application scope of artificial intelligence identification technology. This paper focuses on how to efficiently optimize the model of English translation artificial intelligence scoring algorithm by DNN, specifically studying the DNN model, by studying the mathematical model and algorithm flow of the DNN optimization algorithm, and the basic principle of the DNN model; Based on the DNN model, a learning ability analysis model of English translation algorithm is proposed. Experiments show that this model can optimize the artificial intelligence scoring algorithm of English translation.

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Design of an adaptive fuzzy-neural inference system-based control approach for robotic manipulators

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Applied Soft Computing 2023年第PartA期149卷

作者： Barhaghtalab, Mojtaba Hadi Sepestanaki, Mohammadreza Askari Mobayen, Saleh Jalilvand, Abolfazl Fekih, Afef Meigoli, Vahid Department of Electrical Engineering Faculty of Engineering University of Zanjan Zanjan Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin640301 Taiwan Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA70504 United States Department of Electrical Engineering Faculty of Engineering Persian Gulf University Bushehr Iran

This paper proposes an adaptive fuzzy-neural inference system (ANFIS)-based control approach for a six degrees of freedom (6-DoF) robotic manipulator. Its main objective is to guarantee the error convergence of the controlled system in the presence of uncertainties and unknown disturbances. The suggested controller is a parallel combination of an ANFIS network with a proportional-integral-derivative (PID) controller. The ANFIS system is used as an estimator to approximate a part of the system and then applied as the feedback linearization in the suggested control structure. The convergence of system errors to zero was proven using Barbalat's lemma. The suggested control law combines the simplicity and ease of implementation of PID control with the estimation properties of ANFIS networks. The suggested approach was evaluated using a simulation study and further validated experimentally using the 6-DoF IRB-120 robotic manipulator (IRB-120-RM). The obtained results confirmed its superior performance and suitability for practical implementation to industrial actuators. © 2023 Elsevier B.V.

关键词： Feedback linearization

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Time-Resolved Hanbury Brown–Twiss Interferometry of On-Chip Biphoton Frequency Combs Using Vernier Phase Modulation

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Physical Review Applied 2023年第3期19卷 034019-034019页

作者： Karthik V. Myilswamy Suparna Seshadri Hsuan-Hao Lu Mohammed S. Alshaykh Junqiu Liu Tobias J. Kippenberg Andrew M. Weiner Joseph M. Lukens School of Electrical and Computer Engineering and Purdue Quantum Science and Engineering Institute Purdue University West Lafayette Indiana 47907 USA Quantum Information Science Section Oak Ridge National Laboratory Oak Ridge Tennessee 37831 USA Electrical Engineering Department King Saud University Riyadh 11421 Saudi Arabia Institute of Physics Swiss Federal Institute of Technology Lausanne (EPFL) Lausanne 1015 Switzerland Research Technology Office and Quantum Collaborative Arizona State University Tempe Arizona 85287 USA

Biphoton frequency combs (BFCs) are promising quantum sources for large-scale and high-dimensional quantum information and networking systems. In this context, the spectral purity of individual frequency bins will be critical for realizing quantum networking protocols like teleportation and entanglement swapping. Measurement of the temporal autocorrelation function of the unheralded signal or idler photons comprising the BFC is a key tool for characterizing their spectral purity and in turn verifying the utility of the biphoton state for networking protocols. Yet the experimentally obtainable precision for measuring BFC correlation functions is often severely limited by detector jitter. The fine temporal features in the correlation function—not only of practical value in quantum information, but also of fundamental interest in the study of quantum optics—are lost as a result. We propose a scheme to circumvent this challenge through electro-optic phase modulation, experimentally demonstrating time-resolved Hanbury Brown–Twiss characterization of BFCs generated from an integrated 40.5-GHz Si3N4 microring, up to a 3×3-dimensional two-qutrit Hilbert space. Through slight detuning of the electro-optic drive frequency from the comb’s free spectral range, our approach leverages Vernier principles to magnify temporal features, which would otherwise be averaged out by detector jitter. We demonstrate our approach under both continuous-wave and pulsed-pumping regimes, finding excellent agreement with theory. Our method reveals not only the collective statistics of the contributing frequency bins but also their temporal shapes—features lost in standard fully integrated autocorrelation measurements.

关键词： Quantum coherence & coherence measures Quantum communication Quantum correlations in quantum information Quantum entanglement Quantum information processing Quantum networks Quantum optics

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Lightweight mediated quantum key distribution

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Optik 2023年 287卷

作者： Hwang, Tzonelih Chen, Yen-Jie Tsai, Chia-Wei Kuo, Cheng-Ching Chen, Ming-Jun Department of Computer Science and Information Engineering National Cheng Kung University No. 1 University Rd. Tainan City70101 Taiwan Department of Computer Science and Information Engineering National Taichung University of Science and Technology No.129 Section3 Sanmin Rd. North Dist. Taichung City40401 Taiwan

Inspired by the semi-quantum protocols, this paper defines the lightweight quantum security protocols, in which lightweight participants can only perform at most two out of four very lightweight quantum operations. Subsequently, this study proposes a Lightweight Mediated Quantum Key Distribution (LMQKD) protocol as an example to show the feasibility and advantage of the lightweight quantum protocol. In the proposed protocol, a dishonest third party (TP) with complete quantum capabilities helps two lightweight quantum users establish a secure key. The lightweight quantum users are allowed to perform only: (1) unitary operations and (2) reflecting qubits without disturbance. The proposed protocol has been showed to be robust under the collective attack. © 2023 Elsevier GmbH

关键词： Quantum cryptography

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PointCG: Self-supervised Point Cloud Learning via Joint Completion and Generation

arXiv

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arXiv 2024年

作者： Liu, Yun Li, Peng Yan, Xuefeng Nan, Liangliang Wang, Bing Chen, Honghua Gong, Lina Zhao, Wei Wei, Mingqiang The School of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China The Shenzhen Institute of Research Nanjing University of Aeronautics and Astronautics Shenzhen China The Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing China Urban Data Science section Delft University of Technology Delft Netherlands The Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Hong Kong

The core of self-supervised point cloud learning lies in setting up appropriate pretext tasks, to construct a pre-training framework that enables the encoder to perceive 3D objects effectively. In this paper, we integrate two prevalent methods, masked point modeling (MPM) and 3D-to-2D generation, as pretext tasks within a pre-training framework. We leverage the spatial awareness and precise supervision offered by these two methods to address their respective limitations: ambiguous supervision signals and insensitivity to geometric information. Specifically, the proposed framework, abbreviated as PointCG, consists of a Hidden Point Completion (HPC) module and an Arbitrary-view Image Generation (AIG) module. We first capture visible points from arbitrary views as inputs by removing hidden points. Then, HPC extracts representations of the inputs with an encoder and completes the entire shape with a decoder, while AIG is used to generate rendered images based on the visible points' representations. Extensive experiments demonstrate the superiority of the proposed method over the baselines in various downstream tasks. Our code will be made available upon acceptance. Copyright © 2024, The Authors. All rights reserved.

关键词： Self-supervised learning

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CMOS photonic integrated source of ultrabroadband polarization-entangled photons

arXiv

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arXiv 2024年

作者： Miloshevsky, Alexander Cohen, Lucas M. Myilswamy, Karthik V. Alshowkan, Muneer Fatema, Saleha Lu, Hsuan-Hao Weiner, Andrew M. Lukens, Joseph M. Quantum Information Science Section Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Research Technology Office and Quantum Collaborative Arizona State University TempeAZ85287 United States

We showcase a fully on-chip CMOS-fabricated silicon photonic integrated circuit employing a bidirectionally pumped microring and polarization splitter-rotators tailored for the generation of ultrabroadband (>9 THz), high-fidelity (90–98%) polarization-entangled photons. Spanning the optical C+L-band and producing over 116 frequency-bin pairs on a 38.4 GHz-spaced grid, this source is ideal for flex-grid wavelength-multiplexed entanglement distribution in multiuser networks. Copyright © 2024, The Authors. All rights reserved.

关键词： Polarization

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Efficient and secure semi-quantum private comparison protocol using three-particle GHZ-like states against participant attack

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Modern Physics Letters A 2024年第10期39卷

作者： Yang, Chun-Wei Huang, Yu-Yun Lin, Jason Tsai, Chia-Wei Master Program for Digital Health Innovation China Medical University No. 100 Section 1 Jingmao Road Beitun District Taichung 406040 Taiwan Department of Computer Science and Engineering National Chung Hsing University No. 145 Xingda Road South District Taichung 40227 Taiwan Department of Computer Science and Information Engineering National Taichung University of Science and Technology No. 129 Section 3 Sanmin Road North District Taichung 40401 Taiwan

This study identifies a participant attack vulnerability in Li et al.'s SQPC protocol. The participant attack allows a malicious participant, Bob, to obtain the participant Alice's secret information by intercepting and measuring photons sent to Alice, and later decrypting Alice's encrypted comparison result. An improved SQPC protocol is proposed to address this problem. The key enhancement is introducing a mutual eavesdropping check requiring the third party and participants to verify they obtain the same photon measurement results. This enables detecting participant attacks like the one identified. The SQPC protocol proposed in this study not only withstands attacks from internal participants but also achieves quantum efficiency almost equivalent to Li et al.'s SQPC protocol. Thus, this study presents a more secure SQPC protocol without compromising quantum efficiency. © 2024 World Scientific Publishing Company.

关键词： GHZ-like state participant attack Quantum cryptography semi-quantum private comparison

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Unorthodox parallelization for Bayesian quantum state estimation

arXiv

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arXiv 2025年

作者： Nguyen, Hanson H. Law, Kody J.H. Lukens, Joseph M. School of Electrical Computer and Energy Engineering Research Technology Office Arizona State University TempeAZ85287 United States School of Mathematics University of Manchester ManchesterM13 9PL United Kingdom Elmore Family School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States

Quantum state tomography (QST) allows for the reconstruction of quantum states through measurements and some inference technique under the assumption of repeated state preparations. Bayesian inference provides a promising platform to achieve both efficient QST and accurate uncertainty quantification, yet is generally plagued by the computational limitations associated with long Markov chains. In this work, we present a novel Bayesian QST approach that leverages modern distributed parallel computer architectures to efficiently sample a D-dimensional Hilbert space. Using a parallelized preconditioned Crank–Nicholson Metropolis-Hastings algorithm, we demonstrate our approach on simulated data and experimental results from IBM Quantum systems up to four qubits, showing significant speedups through parallelization. Although highly unorthodox in pooling independent Markov chains, our method proves remarkably practical, with validation ex post facto via diagnostics like the intrachain autocorrelation time. We conclude by discussing scalability to higher-dimensional systems, offering a path toward efficient and accurate Bayesian characterization of large quantum systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Markov chains

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End-To-End Audiovisual Feature Fusion for Active Speaker Detection 14

End-To-End Audiovisual Feature Fusion for Active Speaker Det...

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14th International Conference on Digital Image Processing, ICDIP 2022

作者： Tesema, Fiseha B. Lin, Zheyuan Zhu, Shiqiang Song, Wei Gu, Jason Wu, Hong Interdisciplinary Innovation Research Institute Zhejiang Lab Kechuang Avenue Zhongtai Sub-District Yuhang District Hangzhou China Electrical and Computer Engineering Dalhousie University HalifaxNSB3J 2X4 Canada School of Computer Science and Engineering University of Electronic Science and Technology of China Shahe Campus:No.4 Section 2 North Jianshe Road Chengdu China Ocean College Zhejiang University 866 Yuhangtang Rd Xihu Hangzhou China

ISBN: (纸本)9781510657564

Active speaker detection plays a vital role in human-machine interaction. Recently, a few end-to-end audiovisual frameworks emerged. However, these models' inference time was not explored and are not applicable for real-time applications due to their complexity and large input size. In addition, they explored a similar feature extraction strategy that employs the ConvNet on audio and visual inputs. This work presents a novel two-stream end-to-end framework fusing features extracted from images via VGG-M with raw Mel Frequency Cepstrum Coefficients features extracted from the audio waveform. The network has two BiGRU layers attached to each stream to handle each stream's temporal dynamic before fusion. After fusion, one BiGRU layer is attached to model the joint temporal dynamics. The experiment result on the AVA-ActiveSpeaker dataset indicates that our new feature extraction strategy shows more robustness to noisy signals and better inference time than models that employed ConvNet on both modalities. The proposed model predicts within 44.41 ms, which is fast enough for real-time applications. Our best-performing model attained 88.929% accuracy, nearly the same detection result as state-of-the-art work. © 2022 SPIE.

关键词： Feature extraction

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