Showing 101 - 120 results of 157 for search 'optimal analog computing', query time: 0.10s Refine Results
  1. 101

    Mapping Paleolacustrine Deposits with a UAV-borne Multispectral Camera: Implications for Future Drone Mapping on Mars by Gayantha R. Kodikara, Lindsay J. McHenry, Brian M. Hynek, Jackson K. Njau

    Published 2024-01-01
    “…We benchmarked the onboard image processing capabilities using a Raspberry Pi 5 single-board computer. Processing steps include digital number (DN)-to-radiance conversion, assessment of the best radiance-to-reflectance conversion method, image mosaic creation, DEM generation, calculation of optimal band indices, and selection of the best classification technique. …”
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  2. 102

    Memristor-Based Neuromorphic System for Unsupervised Online Learning and Network Anomaly Detection on Edge Devices by Md Shahanur Alam, Chris Yakopcic, Raqibul Hasan, Tarek M. Taha

    Published 2025-03-01
    “…Threshold optimization and anomaly detection are achieved through a fully analog Euclidean Distance (ED) computation circuit, eliminating the need for floating-point processing units. …”
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  3. 103

    Research on Parameter Distribution Features of Photovoltaic Array under the Cover and Shadow Shading Conditions by Honglu Zhu, Cao Yu, Lingxing Lu, Weiwei Lian, Jianxi Yao, Yang Hu

    Published 2018-01-01
    “…This paper studies the electrical parameter distribution feature of photovoltaic array under different shading conditions by means of analog simulation and empirical testing. Through introducing theoretical computational method of the electrical parameters, it describes the distribution features of the electrical parameters of photovoltaic array. …”
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  4. 104

    INTEGRATION OF DISTRIBUTED INERTIAL NAVIGATION SYSTEMS BUILT AROUND FIBER-OPTIC AND MICROELECTROMECHANICAL SENSORS by A. V. Chernodarov, A. P. Patrikeev, I. I. Merkulova, S. I. Ivanov

    Published 2018-01-01
    “…The current state of airborne measuring-and-computing complexes (MCCs) is characterized by the inclusion of distributed strapdown inertial navigation systems (SINSs) as components of these complexes. …”
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  5. 105
  6. 106

    Very high frequency radio receiver preselector design by E. V. Gurov, S. U. Uvaysov, V. V. Chernoverskaya, R. M. Uvaysov

    Published 2021-12-01
    “…The purpose of the work is to ensure the required characteristics of the preselector in the design process based on computer simulation.Methods. Egor Gurov’s methodology for analog VHF LC-filters was applied to radio receiver preselector design. …”
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  7. 107

    Incidence and Risk Factors for Femoral Malrotation Following Intramedullary Nailing of Trochanteric Fractures: A CT-Based Analysis by Chao Han M.D, Xiao-dan Li M.D, Zhe Han M.D, Qiang Dong M.D

    Published 2025-07-01
    “…All participants underwent postoperative three-dimensional computed tomography (3D CT) and were followed for a minimum of 1 year. …”
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  8. 108

    DIGITAL TOOLS FOR MATCHING QUALIFICATIONS TO THE LEVELS OF THE NATIONAL QUALIFICATIONS FRAMEWORK by Volodymyr Kovtunets, Sergiy Londar, Serhii Melnyk, Oles Kovtunets

    Published 2024-04-01
    “…Therefore, some simple approximation methods for eigenvector computing may be applied using only minimal means of Microsoft Excel or analogous applications. …”
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  9. 109

    Robustly learning the Hamiltonian dynamics of a superconducting quantum processor by Dominik Hangleiter, Ingo Roth, Jonáš Fuksa, Jens Eisert, Pedram Roushan

    Published 2024-11-01
    “…Abstract Precise means of characterizing analog quantum simulators are key to developing quantum simulators capable of beyond-classical computations. …”
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  10. 110

    Low complexity hybrid precoding algorithm for massive MIMO based on modified Newton method by Bo HU, Anding WANG, Guiyi WEI

    Published 2023-11-01
    “…A phase tracking algorithm was proposed for massivemultiple-input multiple-output(MIMO) systems based on the modified Newton (MN) method, which effectively reduced the high computational complexity in traditional high-performance hybrid precoding schemes.The algorithm optimized the analog precoding matrix from the perspective ofsub-dimensional vector recovery.In each sub-dimension optimization, the phase tracking method was used to transform the recovery of the analog precoding vectors into an unconstrained nonlinear optimization problem, which was then solved using the MN method.Concurrently, this strategy led to a marked reduction in the computational intricacy pertaining to both the computation of correction factors and the inversion of the Hessian matrix within the framework of the MN method.This was achieved through the insightful incorporation of Gerschgorin’s Disk theorem and the Hermitian matrix block-inverse lemma.Simulation results show that the proposed algorithm has higher spectral efficiency and lower computational complexity than several conventional high-performance hybrid precoding schemes.…”
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  11. 111

    Edge-guided inverse design of digital metamaterial-based mode multiplexers for high-capacity multi-dimensional optical interconnect by Aolong Sun, Sizhe Xing, Xuyu Deng, Ruoyu Shen, An Yan, Fangchen Hu, Yuqin Yuan, Boyu Dong, Junhao Zhao, Ouhan Huang, Ziwei Li, Jianyang Shi, Yingjun Zhou, Chao Shen, Yiheng Zhao, Bingzhou Hong, Wei Chu, Junwen Zhang, Haiwen Cai, Nan Chi

    Published 2025-03-01
    “…Implementing an edge-guided analog-and-digital optimization method that integrates high efficiency with fabrication robustness, we achieve the inverse design of mode multiplexers based on digital metamaterial waveguides. …”
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  12. 112

    Effects of substrate stiffness and actin velocity on in silico fibronectin fibril morphometry and mechanics. by Seth H Weinberg, Navpreet Saini, Christopher A Lemmon

    Published 2021-01-01
    “…We have previously developed a computational model of FN fibril assembly that recapitulates the morphometry and mechanics of cell-derived FN fibrils. …”
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  13. 113

    Comparing Grid Model Fitting Methodologies for Low-temperature Atmospheres: Markov Chain Monte Carlo versus Random Forest Retrieval by Anna Lueber, Adam J. Burgasser

    Published 2025-01-01
    “…Diamondback models are optimal for early- and mid-type L dwarfs, Elf Owl for mid and late T dwarfs, and SAND for young L dwarfs and L/T transition objects. …”
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  14. 114
  15. 115

    Decoding quantum color codes with MaxSAT by Lucas Berent, Lukas Burgholzer, Peter-Jan H.S. Derks, Jens Eisert, Robert Wille

    Published 2024-10-01
    “…We propose a novel decoder for quantum color codes using a formulation as a MaxSAT problem based on this analogy. Furthermore, we optimize the MaxSAT construction and show numerically that the decoding performance of the proposed decoder achieves state-of-the-art decoding performance on color codes. …”
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  16. 116

    Patient-Specific Bilateral Talus Replacement: A Case Report by Vladimir V. Skrebtsov, Victor G. Protsko, Alexander V. Skrebtsov, Sargon K. Tamoev, Vasilii V. Kuznetsov

    Published 2025-03-01
    “…In case of bilateral pathology, determining the optimal treatment strategy remains a relevant and debatable issue. …”
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  17. 117

    Comparison of the surgical efficacy of total hip replacement versus hemiarthroplasty in the treatment of femoral neck fractures in elderly patients with sarcopenia. by Zhaoyang Yin, Zhuzhi Zhu, Chao Wang, Xiaolong Jia, Xiuqiang Zou

    Published 2025-01-01
    “…<h4>Background</h4>Total hip arthroplasty (THA) and hemiarthroplasty (HA) are common surgical procedures for femoral neck fracture (FNF) in elderly patients; however, optimal treatment options remain controversial. Currently, limited research has compared the effectiveness of THA versus HA, specifically in patients with FNF and sarcopenia.…”
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  20. 120

    Enabling Selective and Tunable Weight Updates in All-InGaZnO 3-Transistor 1-Capacitor Synaptic Circuits for On-Chip Training by Minseung Kang, Mingi Kim, Jaehyeon Kang, Jongun Won, Hyeong Jun Seo, Changhoon Joe, Youngchae Roh, Yeaji Park, Sangbum Kim

    Published 2025-01-01
    “…With the proposed selection method and tunable weight updates, 3T1C synaptic circuit is a promising candidate for scalable large-scale deep neural network accelerators based on analog compute-in-memory technology.…”
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