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检索条件"主题词=Signal Processing Algorithms"

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An Efficient Depth-tracking Method for Live Control of Laser Drilling Process with Optical Coherence Tomography

An Efficient Depth-tracking Method for Live Control of Laser...

引用

IEEE International Conference on Mechatronics and Automation

作者： Tianyi Zhao Yuxin Luo Jinhan Zhao Hongjie Ren Hai Xiang Yifei Liu Yaoyu Ding School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Westa College Southwest University Chongqing China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

Laser drilling has been widely used for fabricating holes in the semiconductor industry due to high throughput and small heat-affected zone. However, it produces varying depths owing to uncertain external conditions and needs a live control at a few kHz rate to handle the fast material removal rate. Optical coherent tomography holds a capacity of in situ acquiring raw interferogram at a high rate (>80 kHz), but the depth extraction is slow (<0.5 kHz) due to the involved heavy Fast Fourier Transform (FFT). To address it, an efficient depth-tracking algorithm is proposed to save the FFT. It searches the depth in the raw interferogram locally with a known last depth given the two truths that only one depth exists and the adjacent depths would not change significantly. The proposed algorithm was proved to expedite the measuring rate to around 3 kHz with a sub-pixel tracking precision. To further secure the rate from the interrupt of operation system, the tracking process is parallelly implemented with a stabilized 50 kHz in a field programmable gate array. The tests were conducted on probe cards with depth variations introduced by offsetting laser focus. The proposed method exhibited the capacity of maintaining a uniform depth.

关键词： Drilling Fast Fourier transforms Optical feedback signal processing algorithms Process control Laser feedback Optical imaging

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Taekwondo action recognition model based on deep learning and key point matching technology

Taekwondo action recognition model based on deep learning an...

引用

signal processing, Communications and Engineering Management Conference (ISPCEM), International

作者： Jin Senbo Guangzhou Tianxing Experimental School Guangzhou China

ISBN: (数字)9798331528676

ISBN: (纸本)9798331528683

In order to solve the problems in Taekwondo action recognition and key point matching, this paper proposes a hybrid matching model that combines YOLOv8 and an improved dynamic time warping (DDTW) algorithm. The model uses YOLOv8 to detect key points in each frame of the video. When the feature points are lost due to occlusion, the model tries to use the information of adjacent frames to compensate. At the same time, in order to reduce jitter, the key point coordinate sequence is smoothed by a low-pass filter. The key frames are matched by the DDTW algorithm, and the action score is calculated according to the best path found by the algorithm. The scoring basis includes the cumulative cosine similarity, action fluency and accuracy. The experimental results show that by combining the images of the three perspectives, the model has achieved significant improvement in recognition accuracy, especially in the key frame combination extracted at the quartile position, the highest recognition accuracy of the front view and the right view reached 92.1% and 94.3% respectively. The method shows strong robustness in noise and speed change processing, and is suitable for motion analysis, rehabilitation training and sports science.

关键词： Training Accuracy Image recognition Heuristic algorithms signal processing algorithms Jitter Solids Robustness Real-time systems Sports

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Component-Wise Squared Factorization

Component-Wise Squared Factorization

引用

IEEE Workshop on Machine Learning for signal processing

作者： Joakim Lefebvre Arnaud Vandaele Nicolas Gillis University of Mons

ISBN: (数字)9798350372250

ISBN: (纸本)9798350372267

The component-wise squared factorization decomposes a matrix as the component-wise square of a low-rank matrix. It can be used to compute the so-called square root rank of a matrix, used in the compact representation of convex polytopes, but also to represent compactly nonnegative data including arithmetic circuits. This paper introduces a coordinate descent algorithm to solve this problem, along with an accelerated variant using extrapolation. We show that it compresses better dense and sparse nonnegative matrices than standard linear low-rank matrix factorization models such as the truncated singular value decomposition (TSVD) and nonnegative matrix factorization (NMF). Then, we explore its application on synthetic matrices generated for experimentation, and also on the slack matrices of regular n-gons and linear Euclidean distance matrices.

关键词： Extrapolation signal processing algorithms signal processing Minimization Polynomials Numerical models Matrix decomposition Sparse matrices Standards Singular value decomposition

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Semi-Passive Intelligent Reflecting Surfaces Aided Channel Estimation for Vehicular Networks

Semi-Passive Intelligent Reflecting Surfaces Aided Channel E...

引用

International Conference on Wireless Communications and signal processing (WCSP)

作者： Yifan Sun Hang Zhou Yingxuan Guo Celimuge Wu Junhui Zhao School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Informatics and Engineering University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

Intelligent Reflecting Surfaces (IRS) have appeared as a cutting edge strategy to augment channel estimation and amplify network efficiency in high-mobility vehicular networks. The semi-passive IRS contains semi-passive and passive elements, and changing the phase of these elements can enhance control of signals precisely. In this paper, the semi-passive IRS aided channel estimation is investigated to mitigate the multipath fading and channel error, thereby improving the achievable rate and channel estimation accuracy. This novel methodology is presented by the implementation of phase optimization of the IRSdynamic channel estimation technique and IRS deployment strategy. In IRS aided channel estimation, the Spatial Base Extended Model (SBEM) algorithm is used to simplify the uplink channel estimation process and the Particle Swarm Optimisation (PSO) the IRS phase to improve the channel estimation accuracy. Simulation result shows the method can to significantly improve the communication efficiency and channel estimation accuracy within the high-mobility vehicular networks.

关键词： Wireless communication Accuracy Simulation Channel estimation signal processing algorithms Complexity theory Vehicle dynamics Uplink Optimization Surface treatment

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Cotton Jassid Infestation Monitoring Using Sentinel-2 MSI, Landsat 9 TIRS, and PlanetScope Imagery with Machine Learning and Data Fusion

Cotton Jassid Infestation Monitoring Using Sentinel-2 MSI, L...

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International Conference on Computer and Applications (ICCA)

作者： Souleymane Bah M. D. Tanguy Mesreil Houegbe Emmanuel Wilfried G. Megnigbeto Vinasetan Ratheil Houndji Bignon Nicanor Kouton N. Gérard Gouwakinnou C. Eugène Ezin Institut de Mathématiques et de Sciences Physiques Université d'Abomey-Calavi Dangbo Bénin BiPLAC Laboratoire d'Ecologie de Botanique et de Biologie végétate Parakou Benin Division protection phytosanitaire Institut de Recherche sur le Coton Parakou Bénin Institut de Formation et de Recherche en Informatique Université d'Abomey-Calavi Abomey-Calavi Benin

ISBN: (数字)9798350367560

ISBN: (纸本)9798350367577

The excessive use of synthetic pesticides in the fields is the cause of numerous problems to human health and biodiversity. Knowing the location and severity of the emergence of pests enables targeted treatment, helping to reduce the use of pesticides. Given that traditional field inspection requires considerable effort with limited effectiveness, remote sensing combined with machine learning is an essential complement for large-scale, efficient monitoring. This study therefore aims to develop a machine learning-based solution for detecting cotton jassids from free satellite imagery data in Alibori, northern Benin. Multispectral and thermal infrared images respectively from the Sentinel-2 and Landsat 9 satellites were fused in the most correlated bands using signal processing algorithms Pseudo Wigner Distribution (PWD), Nonsubsampled Contourlet Transform (NSCT), and Discrete wavelet transform (DWT). Two configurations, in terms of data augmentation, were used. Areas infested by jassids were identified in merged and unmerged satellite images (Sentinel-2, Landsat 9, and PlanetScope, a commercial satellite) using Support Vector Machine (SVM), Random Forest (RF), and CatBoost supervised machine learning algorithms. The green and Thermal Infrared Sensor 1 (TIRS1) bands are the most correlated in configuration 1 and the blue and TIRSI bands in configuration 2 for respectively Sentinel-2 and Landsat 9. The DWT and NSCT signal processing algorithms produced the least Root Mean Square Deviation (RMSE) for image fusion (0.46 for DWT and 0.33 for NSCT). The best result in terms of detecting performance was obtained with the composite treatment of Landsat 9 images and the RF algorithm, with an overall accuracy of 88.23%, an Fl-score of 82%, and a Kappa index of 79.92% in configuration 1 and in configuration 2 for composite treatment of Sentinel-2 an overall accuracy of 92.36%, an Fl-score of 90.75 % and a Kappa index of 86.36% with CatBoost algorithm.

关键词： Radio frequency Support vector machines Satellites Machine learning algorithms signal processing algorithms Landsat Discrete wavelet transforms Satellite images Cotton Monitoring

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Maximizing the Revolutionary Potential of Quantum Computing: Challenges, Opportunities, and Future Directions

Maximizing the Revolutionary Potential of Quantum Computing:...

引用

International Conference on Communications and signal processing

作者： B. Yamini R. Nithyanandhan K. Sudha T Nithya K Vijayakumar R Siva Subramanian Dept of Networking and communications School of Computing College of Engg and Tech SRM Institute of Science and Tech Dept of CSE S A Engineering College Dept of CSBS R.M.D Engineering College Dept of CSE Rajalakshmi Institute of Technology Department of IT Adhiparasakthi Engineering College Melmaruvathur Dept of CSE RMK College of Engg and Tech

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

The discipline of computing known as quantum computing uses the concepts of quantum mechanics to carry out intricate calculations. Quantum computing employs quantum bits, or qubits, which may exist in superposition states and represent both 0 and 1 simultaneously, in contrast to conventional computing, which uses bits to represent information as either 0 or 1. Beyond the capabilities of conventional computers, quantum computing provides the possibility of computations that are performed exponentially more quickly. It is a fascinating and quickly developing topic that has the potential to revolutionize many different scientific fields and businesses. With the potential to revolutionize a number of industries, including computer security, drugs production, Cybersecurity, the financial sector, ML and data science, and electronic science, quantum computing has emerged as a viable paradigm. Quantum cryptography and secure communication protocols improve security in computer security, however creating quantum-resistant encryption methods is a major difficulty. Quantum chemistry simulations and quantum ML have the potential to speed up drug development and advance pharmaceutical research, but integrating them into current processes is difficult. Quantum-resistant cryptographic algorithms, intrusion detection, and safe multi-party computing have the potential to improve security in cyberspace, necessitating further study in this area. In general, overcoming hardware limitations, enhancing qubit coherence, creating effective algorithms, and bridging the theoretical and practical implementation gaps are key to the future of quantum computing. Realizing the revolutionary effect of quantum computing requires collaboration between quantum scientists, subject matter experts, and industrial stakeholders. This review article delivers a thorough summary of the uses, advantages, difficulties, and potential uses of quantum computing in several fields. Further it focusses future resear

关键词： Drugs Electric potential Quantum computing Reviews Qubit signal processing algorithms signal processing

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A Group Authentication Method for Public Transportation Platooning

A Group Authentication Method for Public Transportation Plat...

引用

International Conference on Communications, signal processing, and their Applications (ICCSPA)

作者： Gunes Karabulut-Kurt Kubra Nari-Baykal Enver Ozdemir Department of Electrical Engineering Poly-Grames Research Center Polytechnique Montréal Montréal Canada Cybersecurity Engineering & Cryptography Informatics Institute Istanbul Technical University Istanbul Turkey

ISBN: (数字)9798350384819

ISBN: (纸本)9798350384826

With the rapid progress of the use of autonomous vehicles, the transportation industry is encountering significant transformations. Platooning structures are one of these advancements that help improve the safety of autonomous vehicle networks. These formations hold the potential to reshape the traffic flow of collective vehicles on the roads. Clearly, ensuring the security and privacy of such systems becomes essential. In this work, we propose a protocol that seamlessly integrates into public transportation platooning while prioritizing system security. The main focus of this protocol is providing a lightweight vehicle authentication method for the platoon systems that not only ensures secure authentication but also protects privacy for all involved entities.

关键词： Privacy Protocols Roads Authentication signal processing algorithms Safety Security Fuels Autonomous vehicles Public transportation

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Multi-Hop Routing Based on LEACH in WSN

Multi-Hop Routing Based on LEACH in WSN

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IEEE International Conference on signal processing, Communications and Computing (ICSPCC)

作者： Wei Qian Chen Zanru College of Artificial Intelligence Henan University Zhengzhou Henan China

ISBN: (数字)9798350366556

ISBN: (纸本)9798350366563

In wireless sensor networks, if the cluster head node is too far away from the sink node, it will generate large transmission energy consumption, leading to premature death of the node and reducing the overall network life. In this paper, based on the LEACH cluster routing algorithm, an inter-cluster multi-hop network energy optimization algorithm is proposed-MRLW (Multi-hop Routing based on LEACH in WSN). After dividing the clusters, the node performance evaluation function is constructed through the energy consumption and residual energy of the cluster head nodes; then, the optimal path finding system is constructed; finally, the optimal transmission path of each cluster head node is calculated using convex optimization, which achieves the effect of decreasing the energy consumption of data transmission and prolonging the life of the network. Simulation results show that the proposed MRLW algorithm reduces energy consumption and extends the sensor network's lifetime.

关键词： Energy consumption Wireless sensor networks Simulation Clustering algorithms signal processing algorithms Spread spectrum communication Routing Convex functions Data communication Optimization

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Wind Speed Prediction Method Based on Combined Deep Learning Model

Wind Speed Prediction Method Based on Combined Deep Learning...

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6th International Conference on Intelligent Computing and signal processing (ICSP)

作者： Chuxi Zeng Zhipnig Xia Yihuan Zhou Xi Li Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

The necessity of precise wind speed forecasts is crucial for integrating wind turbines into microgrids. This study introduces a hybrid forecast approach that initially optimizes the key factors of variational modal decomposition (VMD) through the whale optimization algorithm (WOA). Then decomposes the initial wind speed data into intrinsic mode functions (IMFs) using the WOA-VMD method. Secondly, the Pearson correlation coefficient is conducted between IMFs and the initial wind speed data, classifying the IMFs into two groups according to their correlation coefficients. IMFs closely correlated are forecasted utilizing a temporal convolutional network (TCN), while those less correlated are forecasted via a gate recurrent unit (GRU). Finally, the forecasting outcomes from each category are then aggregated to formulate the ultimate forecast results. The hybrid WOA-VMD-GRU-TCN model is tested on actual data from six wind farms across China, the results demonstrate that the proposed model markedly enhances forecast precision, minimizes wind speed prediction errors, and exhibits superior robustness compared to alternative methods.

关键词： Deep learning Correlation coefficient Wind speed Computational modeling signal processing algorithms Predictive models Wind farms Prediction algorithms Data models Wind forecasting

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Static Coordinateometry of Nearby signal Sources Using the Super-Resolution Algorithm MUSIC

Static Coordinateometry of Nearby Signal Sources Using the S...

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Systems of signal Synchronization, Generating and processing in Telecommunications (SYNCHROINFO)

作者： Dmitry Syrovetnik Yevgeniy Glushankov Zahar Kondrashov Dmitry Kirik Dept. of Research and Development Amungo LLC Saint-Petersburg Russia Dept. of Radiosystems and Signal Processing Bonch-Bruevich State University of Telecommunications Saint-Petersburg Russia JSC Progress MRI Moscow Russia Dept. of Research and Development JSC Progress MRI Moscow Russia

ISBN: (数字)9798350373448

ISBN: (纸本)9798350373455

This paper describes a software model for solving the static problem of coordinateometry of nearby signal sources using the MUSIC super-resolution algorithm. The mathematical model permits to simulate the reception of a complex L-band radio signal on a flat equidistant antenna array with 4 antenna elements from several sources with different spatial, power and frequency parameters. Implemented MUSIC super-resolution algorithm gives the most accurate results compared to the beam scanning algorithm and the MVDR (Minimum Variance Distortionless Response) super-resolution algorithm. The coordinateometry algorithm, based on the least squares method, allows you to obtain the coordinates of signal sources with an accuracy of dozens of meters. An application with a graphical interface in the MATLAB environment implements the full functionality of the system: from entering initial parameters to visualizing numerical and graphical results. The obtained results can be applied in solving problems of radio communications, radar and radio navigation.

关键词： Meters Accuracy Superresolution Software algorithms signal processing algorithms Mathematical models Software

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