- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2019 Workshop on Recent Advances in Photonics (WRAP) - Guwahati, India (2019.12.13-2019.12.14)] 2019 Workshop on Recent Advances in Photonics (WRAP) - Spectrum Analysis of Ytterbium-Doped Hybrid Mode-Locked Fiber Laser
摘要： Cloud computing enables customers with limited computational resources to outsource their huge computation workloads to the cloud with massive computational power. However, in order to utilize this computing paradigm, it presents various challenges that need to be addressed, especially security. As eigen-decomposition (ED) and singular value decomposition (SVD) of a matrix are widely applied in engineering tasks, we are motivated to design secure, correct, and efficient protocols for outsourcing the ED and SVD of a matrix to a malicious cloud in this paper. In order to achieve security, we employ efficient privacy-preserving transformations to protect both the input and output privacy. In order to check the correctness of the result returned from the cloud, an efficient verification algorithm is employed. A computational complexity analysis shows that our protocols are highly efficient. We also introduce an outsourcing principle component analysis as an application of our two proposed protocols.
关键词： eigen-decomposition,principle component analysis,singular value decomposition,Cloud computing,secure outsourcing
更新于2025-09-19 17:13:59
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Coupled-Line-Based <i>Ka</i> -Band CMOS Power Dividers
摘要： Cloud computing enables customers with limited computational resources to outsource their huge computation workloads to the cloud with massive computational power. However, in order to utilize this computing paradigm, it presents various challenges that need to be addressed, especially security. As eigen-decomposition (ED) and singular value decomposition (SVD) of a matrix are widely applied in engineering tasks, we are motivated to design secure, correct, and efficient protocols for outsourcing the ED and SVD of a matrix to a malicious cloud in this paper. In order to achieve security, we employ efficient privacy-preserving transformations to protect both the input and output privacy. In order to check the correctness of the result returned from the cloud, an efficient verification algorithm is employed. A computational complexity analysis shows that our protocols are highly efficient. We also introduce an outsourcing principle component analysis as an application of our two proposed protocols.
关键词： eigen-decomposition,principle component analysis,singular value decomposition,Cloud computing,secure outsourcing
更新于2025-09-19 17:13:59
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Polarization Measurement of Time-Energy Entanglement
摘要： The decomposition-based multiobjective evolutionary algorithms (MOEAs) generally make use of aggregation functions to decompose a multiobjective optimization problem into multiple single-objective optimization problems. However, due to the nature of contour lines for the adopted aggregation functions, they usually fail to preserve the diversity in high-dimensional objective space even by using diverse weight vectors. To address this problem, we propose to maintain the desired diversity of solutions in their evolutionary process explicitly by exploiting the perpendicular distance from the solution to the weight vector in the objective space, which achieves better balance between convergence and diversity in many-objective optimization. The idea is implemented to enhance two well-performing decomposition-based algorithms, i.e., MOEA, based on decomposition and ensemble ?tness ranking. The two enhanced algorithms are compared to several state-of-the-art algorithms and a series of comparative experiments are conducted on a number of test problems from two well-known test suites. The experimental results show that the two proposed algorithms are generally more effective than their predecessors in balancing convergence and diversity, and they are also very competitive against other existing algorithms for solving many-objective optimization problems.
关键词： decomposition,Convergence,multiobjective optimization,diversity,many-objective optimization
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE High Power Diode Lasers and Systems Conference (HPD) - Coventry, United Kingdom (2019.10.9-2019.10.10)] 2019 IEEE High Power Diode Lasers and Systems Conference (HPD) - Double-asymmetric-structure 1.5 ?? m high power laser diodes
摘要： Matrix inversion is a fundamental operation for solving linear equations for many computational applications, especially for various emerging big data applications. However, it is a challenging task to invert large-scale matrices of extremely high order (several thousands or millions), which are common in most Web-scale systems, such as social networks and recommendation systems. In this paper, we present a lower upper decomposition-based block-recursive algorithm for large-scale matrix inversion. We present its well-designed implementation with optimized data structure, reduction of space complexity, and effective matrix multiplication on the Spark parallel computing platform. The experimental evaluation results show that the proposed algorithm is efficient to invert large-scale matrices on a cluster composed of commodity servers and is scalable for inverting even larger matrices. The proposed algorithm and implementation will become a solid foundation for building a high-performance linear algebra library on Spark for big data processing and applications.
关键词： linear algebra,parallel algorithm,distributed computing,Matrix inversion,LU decomposition,Spark
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Rooftop PV aspirations of Indiaa??s National Solar Mission and the green building codes: The missing links and the way ahead
摘要： Due to the large-scale and distributed characteristics of increasing renewable energy resources, dynamic economic emission dispatch (DEED) of hybrid energy resource system becomes more and more important in the power system operation. This paper proposes a distributed model predictive control (DMPC) method for hybrid energy resources system of dynamic economic optimal dispatch with large-scale decomposition coordination approach. First, the DEED model of hybrid energy resources is converted into predictive control model, which can provide rolling optimization mechanism for dealing with intermittent energy resources optimization. Second, predictive control model is decomposed into several subsystems with Lagrangian multipliers for coordinating those subsystems, which can greatly decrease the computational complexity. Third, due to the randomness or uncertainty of intermittent power generation, model predictive control can dynamically optimize random or uncertainty problem with rolling optimization mechanism. Furthermore, adaptive dynamic programming is utilized to solve those subsystem optimization problems, which can optimize the random or uncertain problem in real-time condition. In the optimization process, probability constraint is converted into deterministic constraint with its probability density function, and system load balance can be properly handled with coupled coarse-fine constraint-handling technique. According to the obtained results in the case studies, the proposed DMPC can optimize the DEED of hybrid energy resources well combining with the large-scale decomposition-coordination approach, while greatly decreasing the optimization complexity and computation time, which reveals that the proposed method can provide an alternative way for solving the DEED problem of hybrid energy resources.
关键词： large-scale decomposition-coordination,Renewable energy resources,model predictive control,dynamic economic emission dispatch
更新于2025-09-19 17:13:59
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Deep Learning for Computational Mode Decomposition in Optical Fibers
摘要： Multimode ?bers are regarded as the key technology for the steady increase in data rates in optical communication. However, light propagation in multimode ?bers is complex and can lead to distortions in the transmission of information. Therefore, strategies to control the propagation of light should be developed. These strategies include the measurement of the amplitude and phase of the light ?eld after propagation through the ?ber. This is usually done with holographic approaches. In this paper, we discuss the use of a deep neural network to determine the amplitude and phase information from simple intensity-only camera images. A new type of training was developed, which is much more robust and precise than conventional training data designs. We show that the performance of the deep neural network is comparable to digital holography, but requires signi?cantly smaller efforts. The fast characterization of multimode ?bers is particularly suitable for high-performance applications like cyberphysical systems in the internet of things.
关键词： mode decomposition,deep learning,few-mode ?ber,digital holography
更新于2025-09-19 17:13:59
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Wave packet dynamics in slowly modulated photonic graphene
摘要： Mathematical analysis on electromagnetic waves in photonic graphene, a photonic topological material which has a honeycomb structure, is one of the most important current research topics. By modulating the honeycomb structure, numerous topological phenomena have been observed recently. The electromagnetic waves in such media are generally described by the 2-dimensional wave equation. It has been shown that the corresponding elliptic operator with a honeycomb material weight has Dirac points in its dispersion surfaces. In this paper, we study the time evolution of the wave packets spectrally concentrated at such Dirac points in a modulated honeycomb material weight. We prove that such wave packet dynamics is governed by the Dirac equation with a varying mass in a large but ?nite time. Our analysis provides mathematical insights to those topological phenomena in photonic graphene.
关键词： Photonic graphene,Dirac points,Bloch decomposition,Honeycomb structure
更新于2025-09-19 17:13:59
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[IEEE 2019 44th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) - Paris, France (2019.9.1-2019.9.6)] 2019 44th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) - The Upper Branch Broadening in Ultrastrongly Coupled THz Landau Polaritons
摘要： In this paper, we propose a virtual spatial modulation (VSM) scheme that performs index modulation on the virtual parallel channels resulting from the singular value decomposition of the multi-input-multi-output channels. The VSM scheme conveys information through both the indices of the virtual parallel channels and the M -ary modulated symbols. We derive a closed-form upper bound on the average bit error probability (ABEP), which considers the impact of imperfect channel estimation. Moreover, the asymptotic ABEP is also studied, which characterizes the error ?oor under imperfect channel estimation and the resulting diversity order as well as the coding gain under perfect channel estimation. Computer simulations verify the analysis and show that the VSM scheme can outperform the existing pre-coding aided spatial modulation schemes under the same spectral ef?ciency.
关键词： spatial modulation,average bit error probability,Singular value decomposition (SVD),pre-coding
更新于2025-09-19 17:13:59
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Optical and structural-chemistry of SnS nanocrystals prepared by thermal decomposition of bis(N-di-isopropyl-N-octyl dithiocarbamato)tin(II) complex for promising materials in solar cell applications
摘要： Mixed ligand precursor complex bis(N-di-isopropyl-N-octyl dithiocarbamato)tin(II) complex was synthesized from its respective dithiocarbamate ligands, characterized and thermalized through thermogravimetric analysis to yield tin sulfide (SnS) nanocrystals. The thermal decomposition pattern was recorded as a function of the required temperature for the formation of the SnS nanocrystals at 360 °C. The SnS nanocrystals were characterized using optical, vibrational, structural and morphological analyses instruments. The obtained orthorhombic phase SnS nanocrystals showed indirect and direct optical energy band gaps close to the 1.5 eV of the bulk SnS.
关键词： SnS nanocrystals,Thermal decomposition pattern,Mixed ligand precursor complex,Orthorhombic phase,Thermogravimetric analysis
更新于2025-09-19 17:13:59
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[IEEE 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - Rome, Italy (2019.6.17-2019.6.20)] 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - A Singular Value Decomposition Based Approach for Classifying Concealed Objects in Short Range Polarimetric Radar Imaging
摘要： In current research one of the main challenges in short range synthetic aperture radar (SAR) is electrically small structures and objects, which tend to unclear reinforced or through the wall objects, object orientation angle, and obscure contribution to extract the position of concealed multiple small objects. In this paper, ultra-wide-band (UWB) polarimetric radar was used to study reinforced objects and for estimation of object angle at short range. Electrically small 1D periodic mesh, 2D periodic meshes and di?erently oriented small objects or meshes could not be distinguished in conventional SAR images. A radar system with transmit and receive antennae mounted on a two dimensional scanning grid was used. The aim is non-destructive testing of built structures, in concrete slab manufacturing and for use in the renovation process. UWB short range radar data and images corresponding to di?erent polarization states were analysed by using singular value decomposition (SVD). To perform decomposition, the proposed approach applies SVD to image data matrices produced from the back projection algorithm (BPA) to classify the di?erent objects and identify the object angle. Then, sets of singular-components of di?erent polarization states are analysed to classify objects. Also, the BPA algorithm is performed to construct the object images from the polarimetric radar signals. The object re?ection varied with the polarimetric state of the UWB radar, which contributes to di?erent object signatures (i.e., object intensity) since the object signature depends on the orientation, the size, and the number of objects. Object orientation with respect to the radar system and object anisotropy could be determined from the ratio of the di?erent polarimetric singular-components. This proposed complex data analysis method demonstrates the usefulness of the SVD using BPA in extracting more information about and for classifying an object.
关键词： back projection algorithm (BPA),object classification,ultra-wide-band (UWB) polarimetric radar,Synthetic aperture radar (SAR),singular value decomposition (SVD)
更新于2025-09-19 17:13:59