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检索条件"主题词=Signal Processing Algorithms"

共 43555 条记录，以下是4071-4080 订阅

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Laboratory Test of a Perimeter Monitoring System Based on Optical Fiber Interferometer

Laboratory Test of a Perimeter Monitoring System Based on Op...

引用

Optical Fiber Sensors (LAWOFS), Latin American Workshop on

作者： Filipe Henrique Cardoso Rivael Strobel Penze Luis Paulo Barros Joao Batista Rosolem Fabio Renato Bassan Vitor Diago Francivaldo Silva Neves Alessandro de Andrade Ribeiro Kleber Roberto Pirota DTEC CPQD Campinas ALFASENSE São Bernardo IFGW UNICAMP Campinas

ISBN: (数字)9786589532026

ISBN: (纸本)9798350362725

This article describes the results of laboratory tests of the perimeter monitoring system, which is based on optical interferometry according to the Dual-Michelson principle. The tests were carried out in a controlled laboratory environment. The article presents the results obtained and shows a way to effectively implement the system. The results show that the system has the potential to improve safety and monitoring and provide valuable results in the laboratory that can later be applied in a real environment.

关键词： Optical interferometry Optical fiber sensors Accuracy Statistical analysis Heuristic algorithms Laboratories signal processing algorithms

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An Enhanced Conjugate Gradient Algorithm for Solving Unconstrained Optimization and Image Restoration Problems

An Enhanced Conjugate Gradient Algorithm for Solving Unconst...

引用

Innovative Approaches in Smart Technologies (ISAS), International Symposium on

作者： Basim A. Hassan Hisham M. Khudhur Ayman W. Jasim Department of Mathematics College of Computers Sciences and Mathematics University of Mosul Mosul IRAQ

ISBN: (数字)9798331540104

ISBN: (纸本)9798331540111

In order to address unconstrained optimization problems, conjugate gradient methods are frequently employed. When considering the unconstrained optimization issue, the accelerated conjugate gradient approach yields better numerical results than the conjugate gradient method. In this study, we introduce a modified conjugate gradient method that uses Wolfe line search to determine the direction of descent. We prove that the proposed method is globally convergent in modest settings. Numerical evidence indicates the significance of the proposed technique for our test functions. and also that the algorithm’s effectiveness is further validated through its application to image restoration problems, where it achieves superior results in terms of peak signal-to-noise ratio and structural similarity index measure.

关键词： Gradient methods Machine learning algorithms PSNR signal processing algorithms Machine learning signal processing Image restoration Indexes Data mining Optimization

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From Coherent Communications to Quantum Security: Modern Techniques in CV-QKD

From Coherent Communications to Quantum Security: Modern Tec...

引用

Optics and Photonics Conference (SBFoton IOPC), SBFoton International

作者： Valéria Loureiro da Silva Micael Andrade Dias Nelson Alves Ferreira Neto Alexandre B. Tacla Quantum Industrial Innovation (QuIIN) SENAI CIMATEC Salvador Brazil

ISBN: (数字)9798350388176

ISBN: (纸本)9798350388183

Quantum key distribution (QKD) leverages quantum information theory to enable two remote parties to establish a random key with unconditional secrecy. Performing QKD with coherent light states integrates with modern optical communication techniques but presents new challenges. This survey reviews advancements in applying digital signal processing (DSP) techniques, transformative in coherent optical communications, to continuous-variable QKD (CV-QKD). We discuss how DSP methods enhance CV-QKD performance, security, and feasibility. The areas examined include phase estimation, channel equalization, error correction, and noise reduction, highlighting associated challenges and future research directions.

关键词： Surveys Resistance Reviews signal processing algorithms Digital signal processing Optical fiber communication Quantum key distribution Security Quantum communication Photonics

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Design of High-Speed Wideband Digital Upconverter

Design of High-Speed Wideband Digital Upconverter

引用

Electronic Technology and Information Science (ICETIS), International Conference on

作者： Shuqin Wan Yingdan Jiang Wei Wang Tingting Chen Haiqi Lv The 58th Research Institute China Electronics Technology Group Corp. Wuxi China

ISBN: (数字)9798350388343

ISBN: (纸本)9798350388350

The paper proposes a high-speed wideband digital upconverter circuit (DUC) design method, utilizing an optimized CORDIC algorithm to implement a numerically controlled oscillator (NCO) and a four-stage cascade parallel-folded half-band filter (HB-FIR) for interpolation sampling and filtering. Additionally, digital mixing is used to modulate the baseband signal. In the implementation of the circuit design, multi-channel parallel and multiplexing techniques are utilized to reduce hardware costs and power consumption. The final hardware code design for the DUC circuit is completed, with a total area of $550.\overline{1}6^{*}550_{\mathrm{I}^{1}}\mathrm{m}_{9}^{2}$ about 234609 instances, using the $28\text{nm}$ process. The single-channel working frequency can reach $825\text{MH}_{4}$ and with four channels of interleaved sampling, the maximum sampling rate can reach 3 $3\text{GHz}$

关键词： Codes Power demand signal processing algorithms Filtering algorithms signal processing Hardware Wideband

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Gridless 2D Recovery of Lines Using the Sliding Frank-Wolfe Algorithm

Gridless 2D Recovery of Lines Using the Sliding Frank-Wolfe ...

引用

European signal processing Conference (EUSIPCO)

作者： Kévin Polisano Basile Dubois-Bonnaire Sylvain Meignen Jean Kuntzmann Laboratory University Grenoble Alpes and CNRS 5225 Grenoble France

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

We present a new approach leveraging the Sliding Frank-Wolfe algorithm to address the challenge of line recovery in degraded images. Building upon advances in conditional gradient methods for sparse inverse problems with differentiable measurement models, we propose two distinct models tailored for line detection tasks within the realm of blurred line deconvolution and ridge detection of linear chirps in spectrogram images.

关键词： Gradient methods Image resolution Deconvolution Chirp Buildings signal processing algorithms Europe Spectrogram signal resolution

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Multi-Channel Speech Enhancement Using Beamforming and Nullforming for Severely Adverse Drone Environment

Multi-Channel Speech Enhancement Using Beamforming and Nullf...

引用

Acoustics, Speech, and signal processing Workshops (ICASSPW), IEEE International Conference on

作者： Seokhyun Kim Won Jeong Hyung-Min Park Department of Electronic Engineering Sogang University Seoul Republic of Korea Department of Artificial Intelligence Sogang University Seoul Republic of Korea

ISBN: (数字)9798350374513

ISBN: (纸本)9798350374520

In this paper, we present an end-to-end neural beamforming method for multi-channel speech enhancement in drone environments with severe noise levels. In flying drone environment, recording with microphones attached to the drone creates a situation where the proximity and intensity of propeller and motor noise result in a low signal-to-noise ratio (SNR) compared to the target speech. EaBNet is a Deep Neural Network (DNN) based beamforming that utilizes embedding and beamforming modules to address the inherent uninterpretability in previous end-to-end beamforming models. EaBNet utilizes spatial information for speech enhancement and seeks additional improvement through PostNet. Building upon EaBNet, we incorporate a module inspired by the structure of the Generalized Sidelobe Canceller (GSC) algorithm to estimate the spatial information of ego-noise through nullforming. Additionally, we suggest estimating the spectral features of nullforming estimation outputs in addition to the beamforming output and for the input of the PostNet to achieve higher performance. As a result, it was confirmed that performance improved through these two methods.

关键词： Array signal processing Propellers signal processing algorithms Artificial neural networks Speech enhancement Feature extraction Recording

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Enhanced Civilian Airport Detection with Optical Imaging and YOLOv9

Enhanced Civilian Airport Detection with Optical Imaging and...

引用

Intelligent signal processing and Effective Communication Technologies (INSPECT), IEEE International Conference on

作者： Ramesh Kumar Panneerselvam Bhuvan Deep Arekapudi Nagur Vali Shaik Department of CSE V R Siddhartha Engineering College Vijayawada India

ISBN: (数字)9798350379525

ISBN: (纸本)9798350379532

This project focuses on advancing civilian airport detection worldwide through the integration of optical imaging technology and the YOLOv9 deep learning architecture. Manual methods for identifying civilian airports using satellite images are slow, expensive, and prone to errors, posing challenges in urban planning, transportation management, and aviation security. To overcome these limitations, this project proposes an automated system that leverages high-resolution satellite imagery and advanced object detection algorithms. By integrating optical imaging data with the YOLOv9 model, this project enables quick and accurate detection and classification of civilian airports. With features including AI cameras, detectors, and automatic separators, this project offers a cost-effective approach to airport detection, catering to both large and small-scale facilities. By addressing the inefficiencies in current airport detection methods, this project aims to enhance, accuracy, and cost-effectiveness in civilian aviation surveillance and infrastructure planning.

关键词： Accuracy Surveillance Urban planning Transportation signal processing algorithms signal processing Airports Optical imaging Satellite images Planning

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Successive Difference Mode Decomposition for Rotating Machine Fault Diagnosis

Successive Difference Mode Decomposition for Rotating Machin...

引用

Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), International Conference on

作者： Chao Teng Zuogang Shang Xuechun Bai Ruqiang Yan School of Mechanical Engineering Xi'an jiaotong university Xi'an China

ISBN: (数字)9798331529192

ISBN: (纸本)9798331529208

signal processing methods are widely used in fault diagnosis and are known for their strong interpretability. Among them, signal adaptive decomposition algorithms are used to extract the features of fault signals. As an effective adaptive decomposition algorithm, difference mode decomposition divides the signals into three components using spectrum weighting. However, it can only separate mixed fault components and is not suitable for multi-class fault diagnosis tasks. This paper presents a successive difference mode decomposition method, which first defines the reference component and concerned component (fault features) based on the differences in fault. Then, the corresponding filter indexes are solved through iterative convex optimization at each layer. Finally, signals are decomposed into multiple fault components corresponding to different fault sources. The white noise replacement module is further proposed to solve the gradient vanishing problem introduced by successive decomposition. The effectiveness of this method is validated on real datasets.

关键词： Fault diagnosis Rotating machines signal processing algorithms Training data White noise Feature extraction Real-time systems Iterative methods Indexes Time-domain analysis

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Real-time Audio Recognition for Hearing Impaired

Real-time Audio Recognition for Hearing Impaired

引用

Artificial Intelligence For Internet of Things (AIIoT), International Conference on

作者： Muralidhar Peddi S H V Harsha Vardhan Giridhar Peddi Satwik Ponnam C Rani M Rajesh Kumar School of Electronics Engineering Vellore Institute of Technology Vellore India Electrical Engineering University of California Riverside Riverside USA Computer Science Arizona State University Tempe USA School of Electrical Engineering Vellore Institute of Technology Vellore India

ISBN: (数字)9798350372120

ISBN: (纸本)9798350372137

Audio recognition technology has seen significant advancements in recent years, offering promising solutions to improve communication and accessibility for deaf individuals. This paper explores the landscape of audio recognition technologies tailored specifically for the deaf community. It delves into the challenges faced by deaf individuals in everyday communication scenarios and how innovative audio recognition systems can mitigate these challenges. The abstract discusses various approaches, including speech-to-text systems, sound recognition algorithms, and real-time captioning tools, highlighting their effectiveness and limitations in facilitating seamless communication for deaf individuals. Furthermore, it examines the integration of machine learning and artificial intelligence techniques in enhancing the accuracy and adaptability of audio recognition systems for diverse environments and user preferences. Additionally, the abstract explores the potential socio-economic impacts of the widespread adoption of audio recognition technologies in empowering deaf individuals, fostering inclusion, and promoting equal opportunities in education, employment, and social interactions.

关键词： Training Accuracy signal processing algorithms Switches Real-time systems User experience Robustness

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Exploiting Dynamic Phase Information for Respiration Monitoring During Sleep via WiFi

Exploiting Dynamic Phase Information for Respiration Monitor...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Hongyang Zhuo Tianyu Zhong Xianda Wu Baoxian Yu Shen Feng Qinghua Zhong Han Zhang School of Physics and Telecommunication Engineering South China Normal University China Nanyang Technological University Singapore Singapore School of Electronics and Information Engineering South China Normal University China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Respiration monitoring especially during sleep is essential for diagnosing the symptoms of sleep-related diseases. Recently, compared to the conventional wearable devices, WiFi signals can provide a better sensing way with comfortable and convenient benefits. However, the static components caused by static objects closed to WiFi devices significantly limit the detection performance of the respiration sensing. To address this issue, by exploiting the dynamic phase information of WiFi channel state information, we propose a method for extracting the respiration signal. Specifically, we first use the nonlinear least squares fitting to eliminate the static component in WiFi signals. Then, we use principal component analysis to extract the respiration-related dominant component to against the relatively large noise, i.e., the low sensing-signal-to-noise ratio. Our approach has been evaluated on a dataset of 11 participants. Results indicate that it outperforms existing state-of-the-arts in estimating respiration rate, achieving a mean absolute error of less than 0.3 bpm (breaths per minute) across sleep postures.

关键词： Performance evaluation Heuristic algorithms Noise signal processing algorithms Sensors Data mining Wearable devices Wireless fidelity Monitoring Principal component analysis

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