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4th International Conference on Signal processing and Machine Learning, CONF-SPML 2024

作者： Tang, Qiteng Harbin Institute of Technology Shenzhen Electronics and Information Engineering Shenzhen China

ISBN: (纸本)9781510674721

In recent years, the rapid advancement of 5G technology has brought to the forefront the pivotal role of Multiple-Input Multiple-Output (MIMO) system algorithms. This paper delves into a comprehensive exploration of two distinct algorithmic approaches within the context of 5G applications for massive MIMO systems. These two approaches are matrix transformation and machine learning, and the following paragraphs will shed light on their respective attributes and intricacies. Matrix transformation is a fundamental technique in MIMO systems, which aims to optimize the transmission of signals by manipulating the channel matrices. This method, while established and reliable, exhibits certain limitations in accommodating the dynamic and complex nature of 5G environments. On the other hand, machine learning algorithms, with their adaptability and capacity for self-improvement, have gained prominence in recent years. They offer a promising avenue for addressing the challenges presented by 5G MIMO systems, such as handling interference and optimizing resource allocation. In this paper, we provide concrete examples to analyze the strengths and weaknesses of both matrix transformation and machine learning in the context of 5G applications. Furthermore, we explore potential directions for the application of these algorithms and propose areas for improvement, with the ultimate goal of enhancing the efficiency and performance of massive MIMO systems in the evolving landscape of 5G technology. © 2024 SPIE.

关键词： Machine learning

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A 112 Gbps underwater optical wireless communication link based on dual-polarized-16-QAM signal

A 112 Gbps underwater optical wireless communication link ba...

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2024 Photonics North, PN 2024

作者： Khattar, Sonam Singh, Mehtab Abd. Mottaleb, Somia A. Atieh, Ahmad Chandigarh University Mohali India Alexandria Higher Institute of Engineering and Technology Alexandria Egypt Optiwave Systems Inc. Ottawa Canada

ISBN: (纸本)9798350366365

We propose and investigate the transmission performance of a DP-16-QAM signal based underwater optical wireless communicaxtion (UOWC) link. 112 Gbps information is transmitted over a single-laser channel along 10 m UOWC range under pure sea environment with acceptable bit error rate (BER) and constellation of the received signal. Digital signal processing (DSP) algorithms are employed to enhance the quality of the received signal. © 2024 IEEE.

关键词： Quadrature amplitude modulation

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Scheduling algorithm for fidelity of quantum gate circuits 3

Scheduling algorithm for fidelity of quantum gate circuits

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3rd International Conference on Electronic information Engineering and Data processing, EIEDP 2024

作者： Liu, Xudong Xu, Jinchen Lian, Hang Information Engineering University Zhengzhou450001 China

ISBN: (纸本)9781510680531

As quantum computing technology matures, the availability and performance of quantum devices are steadily improving. However, in the NISQ (Noisy Intermediate-Scale Quantum) era, the quantum bit error rate caused by quantum noise remains a significant constraint on computational accuracy and reliability. In quantum operating systems, quantum task scheduling is a core technology crucial for fully leveraging the performance potential of quantum processors. Currently, most multi-processor scheduling algorithms focus on task load balancing and do not directly consider the characteristics of quantum circuits and the differentiated error rates of quantum computing backends. In quantum computing, the impact of noise errors in single-qubit gates, two-qubit gates, and measurement gates on the fidelity of quantum gate circuits is crucial. Therefore, intelligently matching quantum tasks with the characteristics of backend processors to optimize computational accuracy is an urgent problem to be addressed. This paper proposes a new quantum task scheduling algorithm, which matches tasks with backends based on the weight of single-qubit gates, two-qubit gates, and measurement gates in quantum circuits, as well as the error rate characteristics of each quantum computing backend. Experimental results show that the proposed scheduling algorithm for improving the fidelity of quantum gate circuits outperforms static load balancing scheduling algorithms, resulting in a 4.39% increase in the fidelity of quantum tasks. © 2024 SPIE.

关键词： Scheduling algorithms

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Optimal Comparator Adaptive Online Learning with Switching Cost 36

Optimal Comparator Adaptive Online Learning with Switching C...

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36th Conference on Neural information processing systems (NeurIPS)

作者： Zhang, Zhiyu Cutkosky, Ashok Paschalidis, Ioannis Ch. Boston Univ Boston MA 02215 USA

ISBN: (纸本)9781713871088

Practical online learning tasks are often naturally defined on unconstrained domains, where optimal algorithms for general convex losses are characterized by the notion of comparator adaptivity. In this paper, we design such algorithms in the presence of switching cost - the latter penalizes the typical optimism in adaptive algorithms, leading to a delicate design trade-off. Based on a novel dual space scaling strategy discovered by a continuous-time analysis, we propose a simple algorithm that improves the existing comparator adaptive regret bound [ZCP22a] to the optimal rate. The obtained benefits are further extended to the expert setting, and the practicality of the proposed algorithm is demonstrated through a sequential investment task.

关键词： Comparators (optical)

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Small Satellite Electro-optical System (EOS) Technological and Commercial Expansion

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ACTA ASTRONAUTICA 2023年 213卷 355-372页

作者： Gadisa, Dinaol Bang, Hyochoong Korean Adv Inst Sci & Technol KAIST Aerosp Syst & Control Lab ASCL Daejoen 34141 South Korea Korea Adv Inst Sci & Technol Dept Aerosp Engn Aerosp Syst & Control Lab ASCL Daejoen 34141 South Korea Korea Adv Inst Sci & Technol Grad Sch Med Sci & Engn Aerosp Engn Korean Adv Inst Sci & Technol Daejeon 34141 South Korea

The use of electro-optical imaging system for commercial, military, or surveillance missions, as well as space scientific missions, dates back to the first successful operation aboard the US Explorer-6 spacecraft, which was the first spacecraft to capture low-resolution images of the Earth's surface, and the Luna-3 space probe, which was the first spacecraft to send images of the lunar far side, in 1959. The technology underlying EO system have evolved over time, with advances in optics, electronics, and materials science leading to the development of more sophisticated and capable imaging sensors. Furthermore, the technological advances in sensors, optics, mechanics, material, signal and image processing algorithms have allowed EO payloads to become smaller, lighter, and more efficient while still providing high-quality imagery. Over 840 small spacecraft weighing less than 500 kg were launched, with 80% in the constellation segment and 20% as monolithic satellites (i.e., single spacecraft equipped with an electro-optical imaging instrument launched into space for various missions). In this paper, the electro-optical imaging systems of these spacecraft were reviewed using data from a variety of sources, including peer-reviewed journal publications, conference proceedings, mission webpages, and other publicly available satellite databases. Furthermore, the technological and commercial expansion of small spacecraft (<500 kg) equipped with electro-optical imaging systems, as well as EO-COTS parametric performance values such as GSD, spectral range, field of view, and sensor type, are discussed through 2023, divided by spacecraft type: SSO satellites, Small spacecraft constellation, Deep space spacecraft, and EO commercialization.

关键词： Constellation Commercial-off-the-shelf (COTS) EO imaging Evolution Field of view Ground Sampling Distance Small spacecraft Sensor

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Machine learning-driven optical nanomaterials typical applications in food quality assessment: Present obstacles and future horizons

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Food Science and Human Wellness 2025年

作者： Yujie Yan Jingwei Li Yue Yu Zhongyang Ren Yue Huang Zhanming Li College of Grain Science and Technology， Jiangsu University of Science and Technology College of Ocean Food and Biological Engineering， Jimei University College of Food Science and Nutritional Engineering， China Agricultural University

Complex and variable food systems contain numerous interfering substances that produce intricate analytical signals within the relevant matrices. Analytical detection utilizing optical nanosensing often generates an extensive array of data points， characterized by high dimensionality or complex imaging maps. Consequently， the extraction of meaningful data from these vast datasets has emerged as a significant challenge. The integration of machine learning with optical nanomaterials has exhibited remarkable predictive capabilities and accuracy in the processing， analysis， and extraction of valuable information from large and complex food-related datasets. This review systematically elucidates the synergistic relationship between optical nanosensing and machine learning， encompassing: (1) the signal transduction mechanisms and data acquisition utilizing optical nanomaterials; (2) the design and optimization of nanomaterials driven by machine learning; (3) the applications of machine learning algorithms for food data processing and predictive modeling; and (4) the advancements in collaborative applications of machine learning and optical nanomaterials in food quality analysis. Building on this foundation， the paper addresses the challenges currently confronting research on the application of machine learning-driven optical nanomaterials in food quality analysis， constructs a research framework， and outlines potential directions for future exploration. This review offers novel insights into the integrated application of optical nanomaterials and machine learning， presents innovative solutions for the rapid and real-time detection of food quality， and significantly enhances the depth of research into food quality assessment.

关键词： Machine learning optical nanomaterials food quality convolutional neural networks deep learning food data processing

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Object detection algorithm based on residual deformable convolution pyramid 4

Object detection algorithm based on residual deformable conv...

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4th International Conference on Computer vision and Pattern Analysis, ICCPA 2024

作者： Huang, Bin Wang, Sanqian Li, Linjie Fu, Xiang Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang*** China School of Software Nanchang Hangkong University Nanchang*** China

ISBN: (纸本)9781510682528

Considering the challenges associated with robots in optoelectronic imaging applications, typically require real-time and accurate recognition and localization of targets, especially in complex environments. Due to the potential challenges of noise, blurring, or dense targets in the images obtained by optoelectronic imaging systems, traditional object detection algorithms may face issues such as semantic information loss and difficulty in detecting small targets. By introducing residual deformable convolution structures, feature representation can be enhanced in optoelectronic imaging systems, and the shape of the convolution kernel can be dynamically adjusted to adapt to the non rigid deformation of the target, thereby better capturing the detailed features of small targets. Experimental results exhibit that RAFPN enhances the mAP of object detection algorithms RetinaNet, Faster R-CNN, and GFL by 1.2%, 0.9%, and 1.1% respectively on the MS COCO dataset, effectively enhancing the performance of object detection algorithms in optoelectronic imaging. © 2024 SPIE.

关键词： Optoelectronic devices

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Double-exponential trapezoidal shaping filtering algorithm based on FPGA 4

Double-exponential trapezoidal shaping filtering algorithm b...

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4th International Conference on Advanced algorithms and Signal Image processing, AASIP 2024

作者： Wang, Chaoya Qu, Jinhui Li, Lang Yang, Hua Pan, Anyuan Wang, Shaofei Tang, Bin Zhang, Ying Zhi, Chao Chongqing University of Technology Chongqing Key Laboratory of Optical Fibre Sensing and Photodetection Chongqing400054 China East China University of Technology Nanchang China High-tech Enterprise Research and Development Centre for High-grade Servo Numerical Control System Zhejiang Province Jiaxing China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

With the rapid development of high-precision and high-speed ADC devices, traditional analog processing methods for nuclear pulse signals have gradually exited the historical stage. Digitizing nuclear pulse signals has become the main research direction in multi-channel nuclear energy spectrum measurement systems. The trapezoidal shaping filtering algorithm, as the most used nuclear pulse shaping algorithm, has a certain noise suppression capability. This paper studies the double-exponential trapezoidal shaping filtering method based on FPGA in practical applications and explores its role in further eliminating pile-up effects under high counting rates. © 2024 SPIE.

关键词： Wiener filtering

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Computational optical system design: a global optimization method in a simplified imaging system

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APPLIED OPTICS 2022年第20期61卷 5916-5925页

作者： Li, Jiangyong Zhao, Lin Wu, Xiaoqin Liu, Fei Wei, Yazhe Yu, Chun Shao, Xiaopeng Xidian Univ Sch Optoelect Engn Xian 710071 Peoples R China Xian Key Lab Computat Imaging Xian 710071 Peoples R China Sci & Technol Electroopt Informat Secur Control L Tianjin 300457 Peoples R China

An optical imaging system often has problems of high complexity and low energy transmittance to compensate for aberrations. Here we propose a method to correct aberrations by coupling an optical subsystem with a digital subsystem. Specifically, in the global optimization process, the two subsystems correct their respective, easily handled aberrations so that the final imaging aberration is minimized. We design simple lenses with this method and assess imaging quality. In addition, we conduct a tolerance analysis for the proposed method and verify the effectiveness of deconvolution using a spatially varying point spread function (SVPSF) in the actual imaging process. Simulation results show the superiority of the proposed method compared with the conventional design and the feasibility of simplifying the optical system. Experimental results prove the effectiveness of deconvolution using SVPSF. (C) 2022 Optica Publishing Group

关键词： Digital image processing Image deconvolution Image processing algorithms Image quality Imaging systems Imaging techniques

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Design of intelligent slag removal system in power plant based on image recognition

Design of intelligent slag removal system in power plant bas...

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2024 International Conference on algorithms, High Performance Computing, and Artificial Intelligence, AHPCAI 2024

作者： Fu, Changliang Zhang, Yongbin Xie, Xiaodong Zong, Zhiqiang Wei, Xiao Wang, Xinyue Beijing guodian futong science and technology development co. ltd. Tainjin China

ISBN: (纸本)9781510685840

The accurate identification of large and medium slag in power plant slag transport system has an important impact on the safety, efficiency, environmental protection and economic benefits of power plant. The timely processing of large slag can effectively improve the operation efficiency and maintenance cost of power plant, and with the rapid development of image recognition technology, the recognition of large slag in power plant slag transport system is gradually intelligent. In this paper, based on CenterNet image recognition algorithm, through the adaptive spatial feature fusion module is added in the backbone network, and combined with the feature of the pyramid networks structure. The low-level feature information is fused with the high-level feature information. The loss function is replaced by the distributed focus loss, and the effectiveness of the system is verified by experiments. The results show that the system has good convergence, can accurately identify the size and position of large slag block, can respond to the slag removal command quickly, improve the operation efficiency of the power plant slag delivery system, reduce the manual maintenance cost, and improve the operation safety of the power plant. © 2024 SPIE.

关键词： Detection and tracking algorithms Intelligence systems Target recognition Convolution Image processing Feature fusion Safety Infrared radiation Combustion Thermal modeling

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