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检索条件"主题词=Filtering algorithms"

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Range and Velocity Estimation in Carrier-Aggregation OFDM ISAC Systems

Range and Velocity Estimation in Carrier-Aggregation OFDM IS...

引用

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

作者： Jiahui Zhang Ziyun Chao Fanghao Xia Xinyi Wang Jingxuan Huang Zesong Fei School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

The requirements for high-accuracy sensing in future communication systems and the similarity between communication and sensing systems have given rise to integrated sensing and communication (ISAC). Orthogonal frequency division multiplexing (OFDM) waveform has been widely considered a suitable waveform for ISAC to provide sensing functionality with little change on the existing communication systems. However, the large bandwidth requirements of high-precision sensing are contradictory to the fragmentation of communication spectrum resources. Based on existing carrier aggregation (CA) communication architecture, this paper considers a multi-band ISAC system and proposes a universal sensing signal processing algorithm for a CA-OFDM communication system. Improved IDFT and DFT factors are proposed to construct a joint multiband matching filter for CA ranging and velocity estimation. Finally, simulation results confirm the superiority of the proposed algorithm over state-of-the-art schemes.

关键词： Matched filters OFDM Simulation Discrete Fourier transforms Estimation Signal processing algorithms filtering algorithms Integrated sensing and communication Distance measurement Signal to noise ratio

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An Improved Attention-based BiLSTM for PM2.5 Prediction in Air Environment

An Improved Attention-based BiLSTM for PM2.5 Prediction in A...

引用

IEEE International Conference on Networking, Sensing and Control

作者： Kezhu Wang Jing An Zijian Wang Kefan Wang School of Electrical and Electronic Engineering Shanghai Institute of Technology Shanghai China Shanghai Research Institute forIntelligent Autonomous Systems Tongji University Shanghai China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

The accurate prediction of PM2.5 concentrations in the air is crucial for air quality control and pollution prevention. However, the complexity of air environment data and its time-series characteristics pose significant challenges to this prediction task. This study first employs a random forest algorithm for feature selection to identify key features as input variables. Subsequently, a method combining a Butterworth filter with an attention-based bidirectional long short-term memory (BiLSTM) network is proposed for predicting PM2.5 concentrations. The model smooths the input sequence using a Butterworth filter to remove outliers, and extracts useful information from complex long-term dependencies through a bidirectional long short-term memory (BiLSTM) network based on the attention mechanism. Experimental results demonstrate that this method outperforms other similar approaches.

关键词： Recurrent neural networks Pollution Prevention and mitigation Input variables filtering algorithms Information filters Feature extraction Prediction algorithms Sensors Long short term memory

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Comparative Analysis of Noise Reduction Filters for the Quality Enhancement of Mammography Images

Comparative Analysis of Noise Reduction Filters for the Qual...

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East-West Design & Test Symposium (EWDTS)

作者： Sh. Kh. Fazilov O.R. Yusupov Kh.S. Abdiyeva M.S. Abduraxmonov A.A. Qodirov Research Institute for Development of Digital Technologies and Artificial Intelligence Tashkent Uzbekistan Department of Software Engineering Samarkand State University Samarkand Uzbekistan

ISBN: (数字)9798331515768

ISBN: (纸本)9798331515775

Enhancement of the mammography image quality is an important step for precise diagnosis and early breast cancer detection. A comparison of different noise reduction filters used on mammography images is presented in this paper. We evaluate the denoising performance of filters such as Gaussian, Median, and Adaptive median filters. In addition to qualitative assessments by qualified radiologists, the study is predicated on quantitative measures like Mean Squared Error (MSE), Discrete entropy, AMBE, (Absolute Average Brightness Error), and Peak Signal-to-Noise Ratio (PSNR). This thorough assessment offers insightful guidance on how to choose the best noise reduction methods to improve the quality of mammography images, which will ultimately contribute to more accurate breast cancer screening and diagnosis.

关键词： Image quality Image segmentation Filters PSNR Noise reduction Measurement uncertainty filtering algorithms Gray-scale Breast cancer Medical diagnostic imaging

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Features of Navigation algorithms for Different Types of Uncrewed Vehicles

Features of Navigation Algorithms for Different Types of Unc...

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International Conference on Management of Large-Scale System Development (MLSD)

作者： Oleg S. Amosov Svetlana G. Amosova Laboratory of Intellectual Control Systems and Modelling V.A. Trapeznikov Institute of Control Sciences of RAS Moscow Russia Laboratory of Cyber-physical Systems V.A. Trapeznikov Institute of Control Sciences of RAS Moscow Russia

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

This paper deals with the peculiarities of navigation algorithms for uncrewed vehicles operating in airspace, on land and water surfaces, and underwater. These peculiarities are due to the available means of measuring navigational parameters, motion models, and communication capabilities between the vehicles. An example illustrates the information processing in an inertial navigation system.

关键词： Machine learning algorithms Atmospheric modeling Neural networks Geophysical measurements Information processing Inertial navigation filtering algorithms Motion measurement Autonomous vehicles Surface treatment

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Increasing the Efficiency of Constructing 3D Models of Objects by Using a High-Speed Digital Filter

Increasing the Efficiency of Constructing 3D Models of Objec...

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Informatics, Electronics, and Radio Engineering (PIERE), International Conference Problems of

作者： Darya A. Grebenshchikova Andrey V. Kamenskiy Dept. of Television and Control Tomsk State University of Control Systems and Radioelectronics Tomsk Russia

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

The work is devoted to increasing the efficiency of constructing 3-dimensional models of objects, using human organs as an example, through the use of preprocessing of the initial data with a high-speed digital filter. The high-speed recursive-separable digital Laplacian filter “truncated pyramid”, previously developed by the authors, was taken as a filter. This filter, through the use of the properties of recursion and separability, reduces the amount of computational costs required for the processing process, however, there is a factor that slows down its operation, its sequential operating algorithm. In the work, the authors modified the structure of the algorithm from sequential to parallel, displaying the basic principles of operation of the parallel architecture of the recursive-separable Laplacian filter “truncated pyramid” for processing images used to build 3- dimensional models of objects. After conducting experimental studies, including testing the architecture on source images and comparing performance with an existing sequential algorithm, results were obtained that confirmed the effectiveness and applicability of the developed architecture to reduce computational costs. Test objects were constructed without processing and with processing with a modified filter, from which visually and due to the increase in the number of points used to form a dense point cloud, it is clear that the generated 3-dimensional models have increased their quality.

关键词： Point cloud compression Solid modeling Visualization Three-dimensional displays Laplace equations Computational modeling filtering algorithms Computational efficiency Digital filters Testing

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An Indoor Positioning Method Using High Probability RSSI

An Indoor Positioning Method Using High Probability RSSI

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International Conference on Computers, Communications, and Systems (ICCCS)

作者： Jinlong Li Joongoo Park Shuyu Cui Jiabin Dong Lila Rana Jungyu Hwang School of Electronic and Electrical Engineering Kyungpook National University Daegu South Korea

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

This paper addresses a novel method for RSSI-based ranging precision in an indoor positioning The main challenge is to overcome the random signal interference to improve the accuracy of the ranging method. In order to overcome the disadvantages of the problem, several approaches have been proposed in numerous sources, such as mean filter, median filter and Gaussian filter algorithms. However, these current methods may not provide satisfactory results in dynamic indoor environments. Therefore, we tackle the problem by presenting an algorithm that improves the RSSI by averaging over multiple high-frequency RSSI observations. For example, fitting a wireless signal fading model based on various correlations between the high-frequency RSSI average and distance. This would allow us to obtain more accurate distance measurements. The results of the experiment show that the method significantly improve the precision without the requirement of additional equipment compared to existing methodologies.

关键词： Wireless communication Wireless sensor networks Measurement errors Accuracy Heuristic algorithms Measurement uncertainty filtering algorithms

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Clinical Research on the Application of Inertial Measurement Units in Respiratory Cycle Measurement

Clinical Research on the Application of Inertial Measurement...

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Rehabilitation Engineering and Assistive Technology (i-CREATe), International Convention on

作者： Yongli Wu Hui Feng Juanjuan Fu Yuqing Han Huaping Pan Jiangning Hospital Affiliated to Nanjing Medical University

ISBN: (数字)9798350355154

ISBN: (纸本)9798350355161

Objective: The purpose of this study is to explore the feasibility of using inertial measurement unit (IMU) sensors to monitor respiratory ***: The study involved monitoring the abdominal wall movements of 8 healthy volunteers for 9 minutes using IMU sensors. Acceleration change signals were extracted conditionally, and the respiratory cycle (Ttot) was calculated Results: The post-filtering algorithm proposed in this study demonstrated high performance in monitoring respiratory cycle time, as evidenced by the Ttot based on waveform recognition, with an average absolute error of 0.2 seconds per respiratory cycle, a correlation of r > 0.88, and a BlandAltman analysis with an average difference of 0.017 seconds. Conclusion: Monitoring respiratory cycles using inertial measurement unit sensors is feasible and can be widely applied in clinical and home settings. This provides a new approach and method for developing low-cost, wearable, real-time, and stable respiratory monitoring systems.

关键词： Measurement units Correlation Inertial navigation filtering algorithms Assistive technologies Real-time systems Sensors Biosensors Biomedical monitoring Monitoring

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Towards Quantum-inspired Evolutionary algorithms for Denoising PCG Signals

Towards Quantum-inspired Evolutionary Algorithms for Denoisi...

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International Conference on Signal Processing and Information Security (ICSPIS)

作者： Lubna Siddiqui Ashish Mani Jaspal Singh Amity School of Engineering and Technology Amity University Noida India Amity Innovation and Design Centre Amity University Noida India Centre for Development of Advanced Computing Chandigarh India

ISBN: (数字)9798350368673

ISBN: (纸本)9798350368680

This document aims to reaffirm the superiority of quantum-inspired evolutionary algorithms(QiEA) over conventional algorithms. The study proposes a novel QiEA with sorted mutation and greedy local restart (SMGLR) algorithm for finding the optimal coefficients of a filter using a multi-objective optimization function. PCG signals sourced from the Washington Hearts Sounds and Murmurs database and the Michigan Heart Sounds database were filtered using this enhanced filter. Comparative analysis was conducted against the proposed algorithm and established techniques such as Wavelet-based denoising and Variable Mode decomposition. Results: The results revealed that the filter designed using QiEA-SMGLR exhibited superior performance in terms of improved Signal-to-Noise Ratio (SNR) in both comparisons. A comprehensive statistical analysis yielded a correlation coefficient of close to 0.99 indicating strong signal integrity. The QiEA-SMGLR algorithm outperforms Wavelet-based and VMD methods by improving the output SNR by 20% to 100%. This variance can be attributed to the intensity of noise introduced. The result reaffirms the hypothesis that the QiEA-SMGLR algorithm is superior in improving signal clarity and precision over traditionally popular techniques. The improvement in the analysis of Phonocardiogram (PCG) signals could help improve patient diagnostics, amidst the fight against global cardiac problems.

关键词： Heart Noise reduction Signal processing algorithms Evolutionary computation filtering algorithms Wavelet analysis Phonocardiography Signal integrity Optimization Signal to noise ratio

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Improving Machine Learning-Based Wi-Fi Fingerprint Technique with Feature Selection and Grid Search Methods

Improving Machine Learning-Based Wi-Fi Fingerprint Technique...

引用

International Conference on Information Technology and Electrical Engineering (ICITEE)

作者： Tanapol Nimnaul Olarn Wongwirat School of Information Technology King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9798350375817

ISBN: (纸本)9798350375824

This paper presents the enhancement of the WiFi-based fingerprint technique for an indoor positioning system applied to a real experimental area. In typical Wi-Fi-based fingerprint techniques, classification algorithms such as k-nearest neighbor (k-NN), decision tree (DT), and random forest (RF) are used for position estimation. However, these algorithms do not perform well with high-dimensional and large datasets. They also face limitations related to overfitting and uninformative features in datasets. This paper overcomes these challenges by deploying feature selection based on filter methods. This process removes uninformative features from the datasets before feeding them to construct a training model. The grid search method is also employed to perform hyperparameter tuning, which is used to construct the outperforming models. The experimental setup involved collecting received signal strength indicators (RSSIs) from access points (APs) in the real indoor environment to create the radio map. The accuracy performance of the proposed methods was tested by employing the feature selection method on the radio map dataset and using the grid search method to find optimized hyperparameters for constructing the training models based on the k-NN, DT, and RF algorithms. The accuracy results were compared with those of non-feature selection and default hyperparameters used for the three algorithms. The computational results demonstrate that the RF algorithm outperforms the other two algorithms. Furthermore, performance is improved when using grid search and feature selection as proposed.

关键词： Radio frequency Training Accuracy Machine learning algorithms Search methods Estimation Fingerprint recognition filtering algorithms Feature extraction Classification algorithms

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Improved Algorithm Based on PMF-FFT in Spread Spectrum Ranging System

Improved Algorithm Based on PMF-FFT in Spread Spectrum Rangi...

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IEEE International Conference on Information Communication and Signal Processing (ICICSP)

作者： Xinyi Yao Kuangjie Jiang Qian Sun Jun Zou School of Electronic Engineering and Optical Engineering Nanjing University of Science and Technology Nanjing Jiangsu Digital Signal Processing Research and Development Center Jiangsu YEE-Space Technology GO.LTD. Nanjing Jiangsu

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

Addressing the deficiencies of traditional acquisition algorithms in spread spectrum ranging signals, this paper introduces a large doppler range fast acquisition algorithm that utilizes partially matched filters and fast Fourier transform for windowing. The mathematical model of PMF-FFT was extensively analyzed, along with its fundamental principles of acquisition. The characteristics of its amplitude frequency response were mathematically derived and analyzed. This paper examines how changes in filter length affect various performance metrics and provides selection criteria. The performance of the improved algorithm was analyzed, showing that windowing significantly mitigates gain attenuation and associated losses in the acquisition system, and using Tong detection method to improve the capture performance of the system.

关键词： Matched filters Fast Fourier transforms Simulation Signal processing algorithms Signal processing filtering algorithms Attenuation Distance measurement Mathematical models Frequency response

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