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arXiv 2024年

作者： Ippet-Letembet, Louis-Charles Xu, Rui-Fu Jeanty, Robin Yao, Zhi Candler, Robert N. Chen, Shih-Yuan Graduate Institute of Communication Engineering National Taiwan University Taipei10617 Taiwan Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States California NanoSystems Institute Los AngelesCA90095 United States Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan

To overcome the physical limitations of electrically small antennas, strain-mediated magnetoelectric antennas have been studied experimentally and theoretically. However, current closed-form analytical models include solely one-dimensional approaches. This paper proposes a two-dimensional closed-form analytical model of a laterally-excited multiferroic antenna. To model thickness-shear vibrations, we propose an extended Mason model to two dimensions. This theory solves unidirectionally-coupled elastodynamics-magnetization dynamics-electrodynamics. Without using the infinitesimal dipole approximation, this model provides a closed-form solution of the radiated electromagnetic field with an explicit dependency of the antenna response on the physical parameters, enabling their optimization. Furthermore, we compare the efficiency-bandwidth product of different multiferroic antennas with Chu’s limit in the Akhiezer regime, which delimits the highest achievable mechanical quality factor for acoustic resonators at GHz frequencies. We show that phonon-phonon coupling of Akhiezer damping is most likely to limit multiferroic antenna radiation, not Chu’s limit. Moreover, judicious choice of materials can enhance the maximum efficiency by more than an order of magnitude. Copyright © 2024, The Authors. All rights reserved.

关键词： Analytical models

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Qubit-state purity oscillations from anisotropic transverse noise

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Physical Review A 2025年第3期111卷 032420-032420页

作者： David A. Rower Kotaro Hida Lamia Ateshian Helin Zhang Junyoung An Max Hays Sarah E. Muschinske Christopher M. McNally Samuel C. Alipour-Fard Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Applied Physics Graduate School of Engineering The University of Tokyo Bunkyo-ku Tokyo 113-8656 Japan Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Center for Theoretical Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA The NSF AI Institute for Artificial Intelligence and Fundamental Interactions Cambridge Massachusetts 02139 USA

We explore the dynamics of qubit-state purity in the presence of transverse noise that is anisotropically distributed in the Bloch-sphere XY plane. We perform Ramsey experiments with noise injected along a fixed laboratory-frame axis and observe oscillations in the purity at twice the qubit frequency arising from the intrinsic qubit Larmor precession. We probe the oscillation dependence on the noise anisotropy, orientation, and power spectral density, using a low-frequency fluxonium qubit. Our results elucidate the impact of transverse noise anisotropy on qubit decoherence and may be useful for disentangling charge and flux noise in superconducting quantum circuits.

关键词： Qubits

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Overview of Speaker Modeling and Its Applications: From the Lens of Deep Speaker Representation Learning

arXiv

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arXiv 2024年

作者： Wang, Shuai Chen, Zhengyang Lee, Kong Aik Qian, Yanmin Li, Haizhou Shenzhen Research Institute of Big Data School of Data Science The Chinese University of Hong Kong Guangdong Shenzhen518172 China Auditory Cognition and Computational Acoustics Lab The Department of Computer Science and Engineering The MoE Key Laboratory of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai200240 China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong

Speaker individuality information is among the most critical elements within speech signals. By thoroughly and accurately modeling this information, it can be utilized in various intelligent speech applications, such as speaker recognition, speaker diarization, speech synthesis, and target speaker extraction. In this overview, we present a comprehensive review of neural approaches to speaker representation learning from both theoretical and practical perspectives. Theoretically, we discuss speaker encoders ranging from supervised to self-supervised learning algorithms, standalone models to large pretrained models, pure speaker embedding learning to joint optimization with downstream tasks, and efforts toward interpretability. Practically, we systematically examine approaches for robustness and effectiveness, introduce and compare various open-source toolkits in the field. Through the systematic and comprehensive review of the relevant literature, research activities, and resources, we provide a clear reference for researchers in the speaker characterization and modeling field, as well as for those who wish to apply speaker modeling techniques to specific downstream tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Self-supervised learning

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Optimization and evaluation of motion sequences of an averaged human motion model by using kinematic techniques and new evaluation methods

Optimization and evaluation of motion sequences of an averag...

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作者： Kitzig, Andreas Demmer, Julia Naroska, Edwin Stockmanns, Gudrun Viga, Reinhard Grabmaier, Anton Niederrhein University of Applied Sciences Faculty of Electrical Engineering and Computer Science Ambient Intelligence Laboratory Reinarzstr. 49 Krefeld47805 Germany Niederrhein University of Applied Sciences Krefeld Germany University of Duisburg- Essen Department of Electronic Components and Circuits Duisburg Germany Duisburg Germany

Signal processing, pattern recognition as well as modelling and simulation require a large amount of reference data, both for the development of new methods and for their evaluation. Depending on the application, the availability of databases is rather low. In the field of biosignal processing with a focus on the functionalization of furniture for nursing and hospital facilities, a database from a motion capturing system (MoCap), and a method to generate averaged human motion sequences was presented in subsequent works by our research group. Evaluations revealed that the averaged motion sequences partly contain artifacts caused by the averaging and thus are not directly usable. To use the averaged motion sequences e.g., in simulation tasks, this paper presents an extension with kinematic methods to combine averaged motion sequences and to suppress and thus optimize inappropriate motion artifacts by error correction. To check whether the results are usable after the processing steps, four evaluation criteria are proposed. The evaluation of the resulting motion sequences shows that sequences are generated which do not fully correspond to human motion sequences but are well suited for simulation tasks. © 2021 by Walter de Gruyter Berlin/Boston.

关键词： Kinematics

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Parametric Amplification of an Optomechanical Quantum Interconnect

arXiv

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arXiv 2022年

作者： Chen, Huo Vives, Marti Metcalf, Mekena Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Connecting superconducting qubits to optical fiber necessitates the conversion of microwave photons to optical photons. Modern experimental demonstrations exhibit strong coupling between a microwave resonator and an optical cavity mediated through phononic modes in a mechanical oscillator. This paradigmatic transduction experiment is bounded by a theoretical efficiency with constant driving amplitudes on the electromagnetic resonators. By adding a parametric drive to the microwave resonator and optical cavity we discover the converted signal through the quantum transducer is amplified, while maintaining a lower level of the added noise. We propose a theoretical framework for time-dependent control of the driving lasers based on the input-output formalism of quantum optics, and solve analytically the transduction efficiency and added noise when the control signals parametrically drive the system. Our results show better transduction efficiency and lower added noise in varying parameter regimes relevant to current transduction experiments. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum optics

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Extended analysis of data cleaning for electrical energy consumption data of public buildings 12

Extended analysis of data cleaning for electrical energy con...

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12th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, MEDPOWER 2020

作者： Jurj, Dacian I. Polycarpou, Alexis Czumbil, Levente Berciu, Alexandru G. Lancrajan, Mircea Barar, Denisa Micu, Dan D. Electrical Engineering Department Technical University of Cluj-Napoca Cluj-Napoca Romania Department of Electrical and Computer Engineering and Informatics Frederick University Nicosia Cyprus Applied Computational Intelligence Babe-Bolyai University Cluj-Napoca Romania

ISBN: (纸本)9781839535635

In the past years both companies and academic’s communities pulled their efforts in generating input that consist in new abstractions, interfaces, approaches for scalability and crowdsourcing techniques. Quantitative and qualitative methods were created with the scope of error reduction and were covered in multiple surveys and overviews in order to cope with outlier detection. The aim of tis paper is to provide an outlier analysis over the consumption data of twelve public buildings from the Technical University of Cluj-Napoca, collected during an EU 2020 Horizon project. © 2020 Institution of engineering and Technology. All rights reserved.

关键词： Electric power utilization

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Qudit Dynamical Decoupling on a Superconducting Quantum Processor

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Physical Review Letters 2025年第5期134卷 050601-050601页

作者： Vinay Tripathi Noah Goss Arian Vezvaee Long B. Nguyen Irfan Siddiqi Daniel A. Lidar Department of Physics and Astronomy University of Southern California Los Angeles California 90089 USA Center for Quantum Information Science and Technology University of Southern California Los Angeles California 90089 USA Quantum Nanoelectronics Laboratory Department of Physics University of California at Berkeley Berkeley California 94720 USA Applied Math and Computational Research Division Lawrence Berkeley National Lab Berkeley California 94720 USA Department of Electrical and Computer Engineering University of Southern California Los Angeles California 90089 USA Department of Chemistry University of Southern California Los Angeles California 90089 USA

Multilevel qudit systems are increasingly being explored as alternatives to traditional qubit systems due to their denser information storage and processing potential. However, qudits are more susceptible to decoherence than qubits due to increased loss channels, noise sensitivity, and crosstalk. To address these challenges, we develop protocols for dynamical decoupling (DD) of qudit systems based on the Heisenberg-Weyl group. We implement and experimentally verify these DD protocols on a superconducting transmon processor that supports qudit operation based on qutrits (d=3) and ququarts (d=4). Specifically, we demonstrate single-qudit DD sequences to decouple qutrits and ququarts from system-bath-induced decoherence. We also introduce two-qudit DD sequences designed to suppress the detrimental cross-Kerr couplings between coupled qudits. This allows us to demonstrate a significant improvement in the fidelity of time-evolved qutrit Bell states. Our results highlight the utility of leveraging DD to enable scalable qudit-based quantum computing.

关键词： Qubits

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Quantifying Apparent Strain for Automatic Modelling, Simulation, Compensation and Classification in Structural Health Monitoring

Quantifying Apparent Strain for Automatic Modelling, Simulat...

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Science and Information Conference, SAI 2020

作者： A-iyeh, Enoch Computational Intelligence Laboratory Department of Electrical and Computer Engineering University of Manitoba WinnipegMBR3T 5V6 Canada

ISBN: (纸本)9783030522483

This work tackles strain simulation and modelling, as well as channel prediction with strain and temperature measurements as output and input, respectively. We mathematically characterize and quantify the most severe influencer of errors in the light of interpreting strain measurements in relation to structural health monitoring, evaluation and integrity. Subsequently, we automatically pinpoint and trace readings to the sensors and channels they issued forth from, for accurate channel identification, calibration and strain compensation and process automation. Classifiers and simulation models are implemented and validated where applicable. © 2020, Springer Nature Switzerland AG.

关键词： Structural health monitoring

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Self-Similarities in Optical Flows

SSRN

引用

SSRN 2022年

作者： Peters, James F. Cui, Enze Department of Electrical & Computer Engineering Computational Intelligence Laboratory University of Manitoba WPGMBR3T 5V6 Canada Department of Mathematics Faculty of Arts and Sciences Adiyaman University Adiyaman02040 Turkey

This paper introduces self-similarity inherent in the minuscule positive and negative lumens flux (lx) of voxels in dominant moving objects in the foreground of triangulated video frames. A {\bf voxel} is a volume picture element in a video frame with coordinates that include an elapsed time component as well as the usual horizontal and vertical components. Persistent voxel self-similarities can be seen in the divergence of triangulated video frame voxel (lx) (spread of luminous intensity levels). The main results introduced in this paper include (1) inherent self-similarity in triangle clusters covering moving objects in the foreground of video frames, (2) self-similarities in voxel lumens flux in maximal nucleus triangle clusters ({\bf MNC}), and (3) every triangulated video frame MNC is a fractal. © 2022, The Authors. All rights reserved.

关键词： Horizontal wells

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A comparative recognition research on excretory organism in medical applications using neural networks

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Multimedia Tools and Applications 2023年

作者： K, Vidhya R, Krishna Priya Vidhyalakshmi, M. Ramesh, S. M. L, Bharathi Kshirsagar, Pravin R. Rajaram, A. Tirth, Vineet Department of Computer Science and Engineering KPR Institute of Engineering and Technology Tamil Nadu Coimbatore641407 India Department of Engineering - Electrical Section University of Technology and Applied Sciences Shinas Campus Oman Department of Electronics and Communication Engineering SRM Institute of Science and Technology Ramapuram Tamil Nadu Chennai600089 India Department of Signal and Image Processing With Computational Intelligence Saveetha School of Engineering Tamil Nadu Chennai600124 India Department of Electricals and Electronics Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India Department of Artificial Intelligence G H Raisoni College of Engineering Nagpur India Department of Electronics and Communication Engineering EGS Pillay Engineering College Nagapattinam India Department of Mechanical Engineering College of Engineering King Khalid University Asir Abha61421 Saudi Arabia

In the current generation, most individuals are facing many health problems even in the elderly stages and one of the severe touch is caused by to digestive system. Usually, the problems in the digestive system transpire due to improper innards that are present inside it. Even though many experts have described effective solutions to overcome such problems no proper outcomes are achieved. Therefore, the proposed method builds an appropriate device that detects the harmful contents in the entire digestive system which records and stores the data for a continuous period. Additionally, the designed device is incorporated with the neural network using five defined layers where the data is divided into mini segments. This type of data segmentation of input images will reduce the amount of loss in the system thus making the system to be operated at reduced cost. Further equal weights are allocated in the hidden layer using reduced control parameters thereby achieving concentrated attack at several periods. To analyze the effectiveness of neural networks parametric cases are performed and the results prove to be very effective in comparison cases for about 68 percentage. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Medical applications

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