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检索条件"主题词=Filtering algorithms"

共 10354 条记录，以下是921-930 订阅

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Design and Performance Analysis of Communication Signal Processing Algorithm Based on Cognitive Radio

Design and Performance Analysis of Communication Signal Proc...

引用

Power, Electrical Engineering, Electronics and Control (PEEEC), International Conference on

作者： Shiyuan Han Feilong Qin Hongjin Zhu School of Automation and Information Engineering Xi’an University of Technology Xi’an Shaanxi China School of Big Data and Artificial Intelligence Chengdu Technological University Chengdu Sichuan China

ISBN: (数字)9798350378917

ISBN: (纸本)9798350378924

This article aims to propose an effective solution to the problem of signal anomaly identification in wireless communication networks. Therefore, a communication signal processing algorithm based on Cognitive Radio (CR) is designed and implemented, and it is optimized with Differential Evolution (DE) algorithm to improve the recognition accuracy and data recovery ability of abnormal signals. The effectiveness and superiority of this method are verified by collecting a large number of wireless communication network signal data for experimental test. The experimental results show that this method can maintain high recognition accuracy and effectively identify and filter out abnormal signals in the network when dealing with a large number of signal data. Furthermore, this method also shows strong ability in error data repair, which can restore the original data more effectively. In addition, the energy efficiency simulation experiment shows that the proposed algorithm has higher detection rate and energy efficiency ratio than the traditional algorithm. Finally, through the signal coverage performance test, the advantages of this method in wireless communication network signal coverage are further verified.

关键词： Degradation Energy consumption Accuracy Signal processing algorithms Maintenance engineering filtering algorithms Throughput Energy efficiency Stability analysis Cognitive radio

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Edge Detection of Plant Root Images Based on Improved Canny Algorithm

Edge Detection of Plant Root Images Based on Improved Canny ...

引用

Progress in Electromagnetic Research Symposium (PIERS)

作者： Tingfang Tan Lihui Wang Wenlong Zhou School of Information and Communication Engineering Hainan University Haikou China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

The acquisition of root images of slope protection plants relies on optical systems. By designing a suitable optical system, the quality and accuracy of root image acquisition can be improved, which provides an important foundation for subsequent edge detection. This paper introduces an improved Canny algorithm designed specifically for detecting edges in plant root images. It addresses the limitations of the traditional Canny algorithm, such as its susceptibility to salt and pepper noise and its inability to accurately capture edge details when the gradient amplitude changes are minor. This algorithm uses hybrid filter instead of traditional Gaussian filtering for filtering processing, effectively removing noise while preserving more edge information. In addition, the method adds gradient calculations in the 45° and 135° directions to retain more detailed edge information in the root system image. Finally, the Otsu algorithm is used to obtain the optimal threshold. The experimental findings demonstrate that, in comparison to conventional techniques, the proposed algorithm reduces sensitivity to noise and improves the extraction of edge information, which is a significant advantage for edge detection and analysis of root images collected by optical systems.

关键词： Optical filters Accuracy Sensitivity Image edge detection Noise filtering algorithms Optical imaging

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Lightweight Single-Channel Speech Enhancement Based on Multi-Frame MVDR Filters with Learnable Parameters

Lightweight Single-Channel Speech Enhancement Based on Multi...

引用

Electronic Communication and Artificial Intelligence (IWECAI), International Workshop on

作者： Huajian Li Zhanheng Zheng School of Information and Communication Guilin University of Electronic Technology Guilin China Ministry of Education Key Lab. of Cognitive Radio and Information Processing (Guilin University of Electronic Technology) School of Information and Communication Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798350386943

ISBN: (纸本)9798350386950

In daily life, noise may interfere with speech signals, thus seriously affecting speech quality and intelligibility. To solve this problem, many traditional methods based on statistical modeling and methods based on machine learning have been proposed. Nevertheless, most of these algorithms inevitably suffer from a drawback: the attenuation of the noise component may lead to some distortion of the speech component in the enhanced signal. In this paper, we estimate the noise covariance matrix and speech interframe correlation vectors by employing DNN networks, and use them to construct a learnable parametric multi-frame MVDR filter as a way to fully utilize the short-term correlation within the speech signal and apply it to single-channel speech enhancement; we also evaluate the method with baseline model, and objectively demonstrate it's excellent performance and the less number of model parameters and computation compared to mainstream models.

关键词： Correlation Machine learning algorithms Computational modeling Noise Machine learning Speech enhancement filtering algorithms

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Improved Pulse Coupled Neural Network based on Maximize SNR for Vessel Extraction

Improved Pulse Coupled Neural Network based on Maximize SNR ...

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Advancements in Power, Communication and Intelligent Systems (APCI), International Conference on

作者： Davinder Paul Singh Ram Murat Singh T. Gopi D Deepa K. Parimala Gandhi Divesh Kumar Department of Computer Science and Engineering Pandit Deen Dayal Energy University Gandhinagar India School of Technology Woxsen University Telangana Department of ECE Annamacharya Institute of Technology and Sciences Hyderabad India Department of ADS St Joseph’s College of Engineering Chennai India Department of Chemistry Nehru Institute of Technology Coimbatore India Department of Electronics and Communication Engineering Graphic Era Hill University Uttarakhand India

ISBN: (数字)9798350363289

ISBN: (纸本)9798350363296

Aiming at the problems of branch loss and fracture in the fundus retinal vessel segmentation algorithm, with improved pulsed coupled neural network (PCNN) is proposed. As the matched filter can maximize the signal to noise ratio even though using the gaussian filter, therefore, it is used for reducing the noise. First, matching filters are used to enhance the retinal image, and then a segmentation algorithm is suggested using a combination of matching filter and PCNN. Finally, the evaluation on DRIVE database demonstrates that the sensitivity, specificity, and accuracy of the algorithm are 0.7310, 0.9640, and 0.9711 accordingly compared with other algorithms. Simulation experiments illustrate that the Matched-PCNN algorithm resolves the effect of low light and optic disc highlight on vessel segmentation, and demonstrates good connectivity between blood vessels.

关键词： Optical filters Matched filters Image segmentation filtering algorithms Optical imaging Retinal vessels Optical sensors

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Improvement of reconstruction accuracy for hardware systems with Finite Rate of Innovation

Improvement of reconstruction accuracy for hardware systems ...

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Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Jingyu Wang Li Ding Tao Zhou School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai PRC

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

In classical Finite Rate of Innovation (FRI) theory, signal reconstruction is initially achieved with precision using the zeroing filter algorithm on noiseless pulse signals. However, with the introduction of noise, the zeroing filter algorithm exhibits reduced robustness when handling signals with low signal-to-noise ratios (SNR). This paper introduces the TLS-ESPRIT algorithm, which enhances robustness against noise to some extent. Additionally, building on the development of an FRI reconstruction system based on C-TEM sampling, this work innovatively proposes a cascaded filter phase compensation method. This method mitigates the nonlinear phase effects of analog filters, thereby improving reconstruction accuracy. Ultimately achieving a reduction in sampling rate while improving reconstruction accuracy.

关键词： Technological innovation Accuracy Buildings filtering algorithms Information filters filtering theory Signal reconstruction Robustness Noise robustness Signal to noise ratio

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A Threshold Authenticated Encryption Scheme for Secure Communications in Aging-in-Place Systems

A Threshold Authenticated Encryption Scheme for Secure Commu...

引用

IEEE International Conference on Communications in China (ICCC)

作者： Jinkun Gui Zeming Zhou Rongxing Lu Mohammad Mamun Faculty of Computer Science University of New Brunswick NB Canada National Research Council of Canada Fredericton NB Canada

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

The global trend toward aging populations shows the significance of Aging in Place (AiP), which necessitates advanced technologies that enhance both the safety and autonomy of the elderly within their familiar environments. In this context, secure and efficient communication within Internet of Things (IoT) networks for AiP systems becomes crucial. In this paper, we present a novel threshold authenticated encryption scheme designed specifically for AiP contexts. Our proposed scheme integrates the EIGamal threshold decryption with a binary fuse filter, effectively minimizing the frequency of communication group key updates thereby reducing communication overhead. Furthermore, our scheme applies the ASCON encryption algorithm to secure messages’ contents, ensuring the transmitted data’s security. Security analysis confirms that our proposed scheme satisfies the security requirements, which ensures confidentiality and integrity. Performance evaluations also validate its efficiency, highlighting its advantages in terms of communication, storage, and computation overheads.

关键词： Performance evaluation Fuses Aging filtering algorithms Market research Encryption Safety

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GPS-VIO Fusion with Online Rotational Calibration

GPS-VIO Fusion with Online Rotational Calibration

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Junlin Song Pedro J. Sanchez-Cuevas Antoine Richard Raj Thilak Rajan Miguel Olivares-Mendez Space Robotics (SpaceR) Research Group Int. Centre for Security Reliability and Trust (SnT) University of Luxembourg Luxembourg Advanced Centre for Aerospace Technologies (CATEC) Seville Spain Signal Processing Systems Faculty of Electrical Engineering (EEMCS) Delft University of Technology (TUD) Delft

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Accurate global localization is crucial for autonomous navigation and planning. To this end, various GPS-aided Visual-Inertial Odometry (GPS-VIO) fusion algorithms are proposed in the literature. This paper presents a novel GPS-VIO system that is able to significantly benefit from the online calibration of the rotational extrinsic parameter between the GPS reference frame and the VIO reference frame. The behind reason is this parameter is observable. This paper provides novel proof through nonlinear observability analysis. We also evaluate the proposed algorithm extensively on diverse platforms, including flying UAV and driving vehicle. The experimental results support the observability analysis and show increased localization accuracy in comparison to state-of-the-art (SOTA) tightly-coupled algorithms.

关键词： Location awareness Accuracy Estimation filtering algorithms Robot sensing systems Calibration Planning

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Sliding Mode Based Model Predictive Controller for Single-Phase Multilevel T-type Inverters with LCL Filter

Sliding Mode Based Model Predictive Controller for Single-Ph...

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IEEE International Conference on Automatica (ICA-ACCA)

作者： Mokhtar Aly Eltaib Abdeen D. Ibrahim Fernanda Carnielutti Margarita Norambuena Mohamed Abdelrahem Ahmed Elsanabary José Rodriguez Facultad de Ingeniería Arquitectura y Diseño Universidad San Sebastián Bellavista 7 Santiago Chile Electrical Engineering Department High Institute for Engineering and Technology in Sohag Sohag Egypt Federal University of Santa Maria (UFSM) Santa Maria Brazil Electrical Engineering department Universidad Tecnica Federico Santa Maria Valparaiso Chile Dept. of Elec. Eng. Faculty of Eng. Assiut University Assiut Egypt Department of Electrical Engineering Port Said University Port Fouad Egypt

ISBN: (数字)9798350378115

ISBN: (纸本)9798350378122

This paper presents an improved sliding mode-based finite control set model predictive controller for grid-tied single-phase multilevel inverter systems with an LCL filter. The proposed controller employs the inherent robustness of sliding mode control (SMC) with the fast dynamic response of the FCS-MPC method for controlling the complex behavior of LCL filter-based grid-tied inverter systems. The LCL-based grid-tied multilevel inverters necessitate the control of inverter side and grid side currents in addition to the grid filter capacitor voltage and DC-link capacitors voltage control/balance. Incorporating FCS-MPC with SMC eliminates the chattering effects in the traditional SMC algorithms. Moreover, incorporating SMC with FCS-MPC enables more robust and stable control performance compared to the conventional FCS-MPC method. The proposed method eliminates the need for weighting factors for DC-link capacitor voltage balance by properly selecting redundant voltage vectors. Simulation results are provided to validate the proposed SMC-based FCS-MPC controller with different active and reactive power injections to the grid.

关键词： Uncertainty Simulation Capacitors Predictive models filtering algorithms Multilevel inverters Robustness Vectors Voltage control Sliding mode control

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Filtered Tensor Ring-Based Algorithm for Low-Rank Image Completion

Filtered Tensor Ring-Based Algorithm for Low-Rank Image Comp...

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International Multidisciplinary Conference on Computer and Energy Science (SpliTech)

作者： Rafał Zdunek Faculty of Electronics Photonics and Microsystems Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (数字)9789532901351

ISBN: (纸本)9798350390797

The issue of image completion has attracted increasing interest in many areas of science and engineering, including smart and information technologies. In this study, we propose a new computational method for a low-rank image completion problem, where an incomplete image has a large number of uniformly distributed missing pixels or a regular missing structure, e.g. a grid. The proposed method combines a low-rank approximation, enforced by the tensor ring decomposition model, with in-line low-pass filtration. The numerical experiments with strongly incomplete images demonstrate high efficiently of the proposed method.

关键词： Location awareness Tensors Image resolution Filtration Computational modeling filtering algorithms Approximation algorithms

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Near-End Listening Enhancement Using a Noise-Robust Linear Time-Invariant Filter

Near-End Listening Enhancement Using a Noise-Robust Linear T...

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International Workshop on Acoustic Signal Enhancement (IWAENC)

作者： Filippo Villani Wai-Yip Chan Zheng-Hua Tan Jan Østergaard Jesper Jensen Department of Electronic Systems Aalborg University Aalborg Denmark Department of Electrical and Computer Engineering Queen’s University Kingston Canada Oticon A/S Smørum Denmark

ISBN: (数字)9798350361858

ISBN: (纸本)9798350361865

In environments with competing sound sources, speech intelligibility can be significantly compromised. This paper addresses the near-end listening enhancement (NELE) problem, i.e., the problem of processing an available clean speech signal in order to maximize its intelligibility when it is subsequently presented to a human listener in an adverse acoustic situation. We propose a time-invariant and low-complexity NELE algorithm that maximizes an approximation of the Speech Intelligibility Index by redistributing speech energy across frequency bands. Unlike existing algorithms, the proposed algorithm incorporates a mechanism that allows it to distinguish between temporally fluctuating and non-fluctuating noise maskers by using only long-term speech and noise statistics. Simulation results show that the proposed method outperforms baseline algorithms, whether time-invariant or time-varying, in a wide range of noise conditions.

关键词： Time-frequency analysis Working environment noise Simulation Noise Nonlinear filters Speech enhancement filtering algorithms Approximation algorithms Acoustics Indexes

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