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检索条件"主题词=Signal Processing Algorithms"

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Wave Dynamic Time Warping Algorithm for Periodic signal Similarity Estimation

Wave Dynamic Time Warping Algorithm for Periodic Signal Simi...

引用

IEEE SENSORS

作者： Evgenia Slivko Gianfranco Mauro Kay Bierzynski Lorenzo Servadei Robert Wille Infineon Technologies AG Neubiberg Germany Chair for Design Automation Technical University of Munich Munich Germany

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

Similarity estimation between periodic biological signals is crucial for vital sign-sensing applications. In this paper, we propose a novel approach for the accurate alignment and similarity estimation of such signals, named wave Dynamic Time Warping (wave DTW), and its variant, wave derivative DTW. Proposed methods take advantage of the inherent structure of periodic signals and align signal segments rather than entire sequences. Wave DTW employs a two-dimensional feature vector, derived from the signal's amplitude envelope and phase, to perform segment point-by-point alignment using DTW. Validation of the proposed algorithms based on Beth Israel Deaconess Medical Center Photoplethysmogram and Respiration Dataset (BIDMC PPG and Respiration Dataset) demonstrates that wave DTW and wave derivative DTW significantly outperform state-of-the-art algorithms DTW and derivative DTW in terms of path misalignment and path warpings and provide a more intuitive signal alignment.

关键词： Accuracy Heuristic algorithms signal processing algorithms Estimation Manuals Biology Vectors Sensors Periodic structures

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End-to-End Through-Wall Human Localization Network Using Raw Radar ADC Data

End-to-End Through-Wall Human Localization Network Using Raw...

引用

IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Wei Wang Naike Du Yuchao Guo Chao Sun Jingyang Liu Rencheng Song Xiuzhu Ye School of Information and Electronics Beijing Institute of Technology Beijing China Anhui Province Key Laboratory of Measuring Theory and Precision Instrument Hefei University of Technology Hefei China Department of Biomedical Engineering Anhui Province Key Laboratory of Measuring Theory and Precision Instrument Hefei University of Technology Hefei China

ISBN: (数字)9798350378214

ISBN: (纸本)9798350378221

The radar signal processing algorithm is one of the core processes in through-wall radar human localization technology. However, traditional algorithms often struggle to adaptively handle low signal-to-noise ratio (SNR) echo signals in challenging and dynamic through-wall application environments. These environments, characterized by complex and varying conditions such as multi-path reflections and signal attenuation through different wall materials, exacerbate the difficulties in accurately localizing human targets. In this paper, we introduce a novel end-to-end through-wall radar human localization network, which directly processes raw radar Analog-to-Digital Converter (ADC) signals without any preprocessing. By bypassing traditional signal processing stages, our approach leverages the raw data to capture more comprehensive information from the environment, allowing for more robust and adaptable localization. To achieve this, we replace the conventional radar signal processing flow with the proposed DFT-based adaptive feature extraction (DAFE) module. This module employs learnable parameterized 3D complex convolution layers, which are specifically designed to extract superior feature representations from ADC signals. The ability to learn implicit features from raw data enables our network to overcome the limitations of traditional preprocessing methods, which often fail to adequately capture the nuances of low-SNR conditions. We rigorously trained and validated our proposed method on extensive data collected in real-world through-wall scenarios. The experimental results confirm the effectiveness and superiority of our approach, demonstrating its potential to significantly improve human localization accuracy in challenging environments.

关键词： Location awareness Training Accuracy Three-dimensional displays Heuristic algorithms signal processing algorithms Radar Feature extraction Radar signal processing signal to noise ratio

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Study on the Model of Network Health Monitoring System in Care and Prevention

Study on the Model of Network Health Monitoring System in Ca...

引用

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

作者： Hailan Gui Changchun Humanities and Sciences College Changchun China

ISBN: (数字)9798331528676

ISBN: (纸本)9798331528683

In this paper, a network health monitoring system based on augmented reality algorithm is designed to provide more efficient health management services for the elderly. Through the integration of interventional nursing and augmented reality technology, the system realizes real-time monitoring, analysis, and dynamic feedback of user health data. Augmented reality algorithms are used to build interactive interfaces that combine virtual and reality to improve user experience and system operability. The algorithm design of health monitoring system focuses on extracting the key features of health data accurately to improve the accuracy of monitoring and early warning. System simulation verifies the effectiveness and stability of the algorithm. Through the processing and analysis of many health data, the simulation results show that the system has strong adaptability and robustness in diverse scenarios. After adopting the system, the response speed of interventional care decision was increased by about 20%, and the accuracy rate of health abnormality detection was increased by 15%. This study provides an innovative technology path for the field of care and prevention, and lays a foundation for the further development of intelligent health monitoring system.

关键词： Accuracy Heuristic algorithms Prevention and mitigation signal processing algorithms Feature extraction Stability analysis Real-time systems Older adults Monitoring Augmented reality

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A Rigid Registration Pipeline for TMJ CBCT Time-Series Images with Removal of Remodel Structures

A Rigid Registration Pipeline for TMJ CBCT Time-Series Image...

引用

International Congress on Image and signal processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Chen Zhong Jupeng Li Jiling Feng Ruohan Ma Gang Li Beijing Jiaotong University Beijing China Peking University School and Hospital of Stomatology Beijing China

ISBN: (数字)9798331507398

ISBN: (纸本)9798331507404

The accurate estimation of structure and position in relation to Temporomandibular Joint (TMJ) is crucial for Temporomandibular Joint Disorder (TMD) diagnosis and treatment. However, existing automatic rigid registration methods, such as Scale Invariant Feature Transform (SIFT), often have some limitations, including reliance on artificial external features, requiring high computational effort, or ignoring the deformation and physiological changes in anatomical structures. To address these problems, we propose a pipeline for TMJ CBCT time-series images to predict the matrix of translations and rotations in rigid registration task. In our proposed pipeline, a segmentation network is employed to eliminate the effects of complex anatomical structures, and a landmark-based 3D rigid registration is adopted for preliminary rigid registration for avoid poor performance on images with large positional variations. Finally, a self-supervised neural network trained on real medial images is used to predict the rotation and translation parameters. Our network is evaluated on 44 pairs of clinical images. SIRS-Net+ achieves an average Dice coefficient of 0.8020 (approximately 8% higher than SIFT) and an average NCC of 0.7264 (about 10% higher than SIFT).

关键词： Image segmentation Accuracy Three-dimensional displays Shape Pipelines signal processing algorithms Anatomical structure Transforms signal processing Registers

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Secure Multi-Party Computation on the Encrypted Network: a Lattice-based Multi-Party Homomorphic Encryption Protocol

Secure Multi-Party Computation on the Encrypted Network: a L...

引用

Communication, Image and signal processing (CCISP), International Conference on

作者： Yikuan Liang Yao Hao Kaijun Wu Yuxiang Chen Science and Technology on Communication Security Laboratory No.30 Research Institute of China Electronics Technology Group Corporation Chengdu China

ISBN: (数字)9798350356656

ISBN: (纸本)9798350356663

With the continuous development of cloud computing technology and the increasing attention of privacy protection, users are not willing to disclose their private data, but also want to benefit from the results of a large number of data analysis. How to process multi-user privacy data in the cloud environment without disclosing personal privacy is an urgent problem that needs to be solved. Multi-Party homomorphic encryption supports the processing of the ciphertext data of different users, and the result of the processing can be decrypted jointly by all users involved in the calculation, which is more suitable for the privacy protection of multi-user data in the cloud environment. In this paper, we design a multi-party homomorphic encryption protocol with low communication complexity, no private channel restriction and users do not need to be online during ciphertext computation. The protocol mainly includes key generation algorithm and multiparty decryption algorithm based on secret sharing and homomorphic encryption, which improves the ciphertext computing capability of multi-user and multi-source data under different key encryption, and provides technical support for secure multi-party computing.

关键词： Data privacy Cloud computing Protocols Data analysis signal processing algorithms signal processing Multi-party computation Complexity theory Homomorphic encryption Protection

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Inter-Camera Color Correction for Multispectral Imaging with Camera Arrays Using a Consensus Image

Inter-Camera Color Correction for Multispectral Imaging with...

引用

IEEE Workshop on Multimedia signal processing

作者： Katja Kossira Jürgen Seiler André Kaup Multimedia Communications and Signal Processing Friedrich-Alexander University Erlangen-Nürnberg (FAU) Erlangen Germany

ISBN: (数字)9798350387254

ISBN: (纸本)9798350387261

This paper introduces a novel method for inter-camera color calibration for multispectral imaging with camera arrays using a consensus image. Capturing images using multispectral camera arrays has gained importance in medical, agricultural, and environmental processes. Due to fabrication differences, noise, or device altering, varying pixel sensitivities occur, influencing classification processes. Therefore, color calibration between the cameras is necessary. In existing methods, one of the camera images is chosen and considered as a reference, ignoring the color information of all other recordings. Our new approach does not just take one image as reference, but uses statistical information such as the location parameter to generate a consensus image as basis for calibration. This way, we managed to improve the PSNR values for the linear regression color correction algorithm by 1.15 dB and the improved color difference (iCID) values by 2.81.

关键词： Sensitivity Image color analysis Multispectral imaging signal processing algorithms Machine learning Cameras Polynomials Calibration Recording Colored noise

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Azimuth Spatially-Varying Phase Compensation for ISAR Based on Non-Uniform Fast Fourier Transform

Azimuth Spatially-Varying Phase Compensation for ISAR Based ...

引用

International Conference on Vision, Image and signal processing (ICVISP)

作者： Jiabo Fan Shuai Shao National Key Laboratory of Radar Signal Processing Xidian University Xi'an China

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

Traditional Inverse Synthetic Aperture Radar (ISAR) imaging algorithms overlook the impact of higher-order rotational phase of target echoes, resulting in poor azimuth focusing and challenges in imaging maneuvering targets. To address this issue, this paper proposes a method for compensating azimuth spatially-varying phase errors based on Non-Uniform Fast Fourier Transform (NUFFT). This method establishes a model for the spatially-varying phase errors of maneuvering targets and utilizes the NUFFT technique to accelerate the rapid compensation of azimuth spatially-varying errors (AVSE) in two-dimensional ISAR images, effectively reducing computational complexity and achieving fast focusing of the images. Experimental results demonstrate that this method is effective and robust for ISAR imaging of maneuvering targets.

关键词： Azimuth Fast Fourier transforms Computational modeling signal processing algorithms Focusing Radar imaging signal processing Robustness Computational complexity Inverse synthetic aperture radar

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Research on Competitive Evaluation Based on Genetic Algorithm

Research on Competitive Evaluation Based on Genetic Algorith...

引用

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

作者： Diandong Liu Lianshan Sun Yongyi Han Hao Tian Shaanxi University of Science and Technology Xi’an China

ISBN: (数字)9798331528676

ISBN: (纸本)9798331528683

Genetic algorithms are machine learning algorithms inspired by the theory of natural evolution. By mimicking the process of natural selection and reproduction, genetic algorithms can provide high-quality solutions to a wide range of problems involving search, optimization, and learning. It can overcome some of the obstacles encountered by traditional search and optimization algorithms, especially for problems with many parameters and complex mathematical representations. To extend its application, this paper applies it to more subjective judging sessions. Firstly, after in-depth analysis, collation, and classification of judging data from several innovation competitions, genetic algorithms are subsequently used to optimize the allocation of works and judging experts, and the current standard score judging scheme is improved by non-linear correction of parameters. The results of the final data experiment show that the model greatly improves the concentration of scores and judging power and provides a reference for similar subjective scenario modelling optimization.

关键词： Technological innovation Machine learning algorithms signal processing algorithms Search problems Data models Mathematical models Classification algorithms Optimization Standards Genetic algorithms

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Research on Complex Street View Detection Algorithm Based on YOLOv8

Research on Complex Street View Detection Algorithm Based on...

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signal processing and Intelligent Computing (SPIC), International Conference on

作者： Haiyang Du Jun Liu School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

The current street scene is becoming more and more complex, with high pedestrian and vehicular traffic and a large number of targets. Aiming at the problems that the accuracy of the current complex street scene-oriented detection algorithms is not satisfactory and the leakage rate of small targets is unstable, the intelligent detection algorithm YOLOv8s- for complex street scenes is proposed, aiming at the intelligent detection of multi-targets in daily street scenes. This study is based on the target detection model of YOLOv8s, proposing a C2f-DCNv2 module that can sample features flexibly; adding a small target detection layer in the head; and using the Shape IoU loss function. The improved algorithm improves the precision, recall, and average accuracy by 2.2%, 3.6%, and 5.0%, respectively, compared with the initial algorithm, and these experimental data validate that this study can have a good performance when targeting the detection task of complex street scenes.

关键词： Performance evaluation Accuracy Pedestrians Shape Urban areas signal processing algorithms Object detection Real-time systems Mobile handsets Detection algorithms

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Subspace Projection Algorithm based on Code Agile Waveform for Folded Clutter Suppression

Subspace Projection Algorithm based on Code Agile Waveform f...

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signal, Information and Data processing (ICSIDP), IEEE International Conference on

作者： Zihao Liu Huayu Fan Zhaopeng Cao Lixiang Ren Quanhua Liu Erke Mao Radar Research Lab Beijing Institute of Technology Beijing China Key Laboratory of Electronic and Information Technology in Satellite Navigation Beijing Institute of Technology Beijing China Yangtze Delta Region Academy of Beijing Institute of Technology Beijing China Chongqing Innovation Center of Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

The Internal Clutter Motion (ICM) results in an expansion of the clutter Doppler spectrum. With conventional waveforms, the presence of range ambiguity causes short-range strong clutter with ICM to be folded into the long-range interval. The folded clutter, along with Doppler expansion, submerges low-speed small targets, significantly affecting the target detection performance of ground-based early warning radar. Agile waveforms improve the distinguishability of echoes from different range intervals by varying the waveform parameters between pulses, enhancing the degree of signal processing. Therefore, this paper proposes a subspace projection algorithm based on code agile waveform to suppress the folded clutter with ICM. First, the clutter subspace is constructed using the echo model of the code agile waveform and the distribution characteristics of clutter in the range-Doppler domain. Next, subspace projection is applied to each range interval, with iterative processing between intervals to achieve folded clutter suppression. Finally, the joint mismatch filtering and Pulse Doppler (PD) processing is performed to realize coherent accumulation in each range interval. The simulations and processing results of real measured data demonstrate the effectiveness of the proposed algorithm in suppressing folded clutter and improving the detection performance of small targets at long-ranges and low-speeds.

关键词： Codes Filtering Radar clutter signal processing algorithms Radar detection signal processing Data models Doppler effect Clutter Projection algorithms

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