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检索条件"主题词=Filtering algorithms"

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Collaborative Calibration Algorithm in Redundant Dual-axis RINS Configuration

Collaborative Calibration Algorithm in Redundant Dual-axis R...

引用

International Conference on Information Fusion

作者： Zhonghong Liang Yuanhan Wang Zhikun Liao Pengcheng Mu Hui Luo Lin Wang College of Advanced Interdisciplinary Studies Nanhu Laser Laboratory National University of Defense Technology Changsha China

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

Dual-axis rotational inertial navigation system (DRINS) can achieve self-calibration of error parameters to improve the navigation performance. However, the traditional self-calibration methods rely on the external reference information. This paper focuses on the dual DRINSs configuration and proposes a collaborative calibration algorithm. Considering the error parameters of redundant DRINS, the 60-D Kalman filter is established, in which the geometric constraint between systems are deployed to establish the observation equation without external reference information. A novel collaborative calibration scheme is designed based on the asynchronous rotation to make all the error states observable. Monte Carlo simulations and real system experiments are conducted to verify the effectiveness of the proposed algorithm. The result shows the algorithm works well.

关键词： Analytical models Monte Carlo methods Heuristic algorithms Collaboration Inertial navigation filtering algorithms Information filters Mathematical models Calibration Kalman filters

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Enhancing Heart Rate Detection Accuracy Through the Kalman Filter Algorithm

Enhancing Heart Rate Detection Accuracy Through the Kalman F...

引用

Technology Innovation and Its Applications (ICTIIA), International Conference on

作者： Mangasa A. S. Manullang Poltak Sihombing Mahyuddin K. M. Nasution dept. Teknik Informatika Fakultas Ilmu Komputer dan Teknologi Informasi Universitas Sumatera Utara Medan Indonesia

ISBN: (数字)9798350351613

ISBN: (纸本)9798350351620

The imperative need for precise heart rate detection, particularly in the early diagnosis of heart conditions, amidst various risk factors like unhealthy lifestyle choices, stress, air pollution, and nutritional imbalances. It advocates for the utilization of the Kalman Filter Algorithm to refine the accuracy of heart rate monitoring systems. By bolstering the stability and precision of these systems, the algorithm aims to surmount challenges inherent in current methods, which often grapple with instability and inaccuracies. Through meticulous comparative analysis, the study showcases a notable reduction in error rates. In heart rate detection through the heart rate detection system, the MAPE percentage of errors found was smaller when using the Kalman Filter during heavy activity, which was 3.51%, compared to 6% without the Kalman Filter. Similarly, in experiments without heavy activity, the error rate was 2.69% with the Kalman Filter, compared to 8.95% without it. This represents an error reduction of approximately 4.37%. These findings underscore the potential of the proposed methodology to significantly propel health monitoring technologies forward, thereby facilitating more dependable and efficient management of heart diseases. Consequently, this research makes substantial strides towards enhancing overall health and elevating the quality of life for individuals at risk of heart disorders, ultimately fostering a healthier society.

关键词： Technological innovation Accuracy Error analysis Propulsion filtering algorithms Heart rate detection Stability analysis Kalman filters Monitoring Stress

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Bearings Fusion using the Cross Entropy Method for Underwater Multitarget Tracking

Bearings Fusion using the Cross Entropy Method for Underwate...

引用

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

作者： Gao Qiang Jiangsu Automation Research Institute Lianyungang Jiangsu China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

In scenarios with an unknown and time-varying number of targets, this paper proposes an underwater multi-target tracking method based on cross-entropy method data association for multi-array bearing fusion. The proposed method constructs a probability distribution over the association space under conditions of uncertain target numbers. Potential solutions for target birth and death, as well as the association between surviving targets and bearing measurements, are generated by random sampling. This approach enhances the tracking capability under conditions of a large and unknown number of targets. Simulation experiments validate the effectiveness of the proposed algorithm and improved performance compared to traditional methods.

关键词： Target tracking Fuses Simulation Signal processing algorithms Signal processing Probability density function filtering algorithms Information filters Probability distribution Entropy

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COA Optimized PEMFC Remaining Useful Life Prediction for CRJ Networks

COA Optimized PEMFC Remaining Useful Life Prediction for CRJ...

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System Simulation Technology and its Application (CCSSTA), IEEE China Conference on

作者： Ze Feng Peng Shi Wenhao Wang Liang Xu Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Tianjin China Tianjin Institute of Metrological Supervision and Testing Tianjin China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

Aiming at the RUL (remaining useful life) prediction problem of PEMFC (Proton Exchange Membrane Fuel Cell), this paper proposes a PEMFC remaining service life prediction model based on the long-nosed raccoon algorithm (COA) optimized deterministic jump cycle (CRJ) network model. After smoothing the data with equal interval sampling and SG convolutional smoothing, the 24 feature variables in the original data of the PEMFC were downscaled by principal component analysis. Then optimal input features were determined by the cumulative contribution rate, and then the optimization of the CRJ network was carried out by using the optimization of the CRJ network’s cyclic ring weights $r_{c}$, jump weights $r_{j}$ and the leakage rate parameter. The optimized CRJ network was used to make a prediction of the RUL of the PEMFC. In the simulation experiments, by comparing with the unoptimized CRJ network and COA-BP network prediction model, the MAE, PMSE and $R^{2}$ of this paper’s method are better, reaching $0.0026104,0.003582$ and 0.94715, respectively.

关键词： Protons Smoothing methods Fuel cells Predictive models filtering algorithms Prediction algorithms Systems simulation Performance analysis Optimization Principal component analysis

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Event-Triggered Distributed State Estimation Based on Asymptotic Kalman-Bucy Filter

Event-Triggered Distributed State Estimation Based on Asympt...

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European Control Conference (ECC)

作者： Irene Perez-Salesa Rodrigo Aldana-López Carlos Sagüés Departamento de Informática e Ingeniería de Sistemas (DIIS) Instituto de Investigación en Ingeniería de Aragón (I3A) Universidad de Zaragoza María de Luna 1 Zaragoza Spain

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Distributed state estimation is a relevant research topic due to its application opportunities in different fields, such as multi-robot cooperation and control of large-scale networked systems. In addition, event-triggering mechanisms have been studied in recent years to reduce communication between network nodes without significantly compromising the desired behavior. In this work, we contribute a distributed algorithm to estimate the state of a stochastic system under event-triggered communication. The proposal uses consensus on the state estimates, and it takes advantage of the asymptotic form of the well-known Kalman-Bucy filter so that only state information needs to be transmitted during the online execution. We provide guarantees of boundedness of the error covariance for the state estimates under event-triggered communication. Moreover, we show that the centralized optimal solution can be recovered when the event threshold is decreased, which is an improvement with respect to existing event-triggered estimators in the stochastic context. Finally, we show via simulation that the proposal effectively reduces communication without sacrificing the quality of the estimates, and it improves performance with respect to previous approaches.

关键词： Estimation error Stochastic systems Europe Mean square error methods filtering algorithms Information filters Error correction codes

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Development of Simple Algorithm to Detect and Filter Motion Artifact Noise in Non Invasive Blood Pressure (NIBP) Measurement

Development of Simple Algorithm to Detect and Filter Motion ...

引用

Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Trio Adiono Rd Elviana La’salina Muhlis Clarence Amadeus Sindy Novaria Cicilya Sinaga School of Electrical Engineering and Informatics Bandung Institute of Technology Indonesia PT. Xirka Dama Persada Indonesia

ISBN: (数字)9798350367331

ISBN: (纸本)9798350367348

Motion artifact is a noise induced by patient during NIBP measurement due to the patient’s intentional or unintentional movements. It can reduce the accuracy of the measurement. In this paper, we will conduct a study to identify, detect, and reduce the motion artifact effect to the NIBP measurement. MATLAB will be used to analyze the measurement signal, detecting and reducing the motion artifact present on the data. Our experiment shows that measurement data corrupted by motion artifacts has larger peaks in their frequency response. To reduce this noise, the noisy measurement signal is fit into a straight line, then the noisy measurement signal is subtracted with this straight line. The method has decreased MAP error by 67.48%, SYS error by 39.28%, and DIA error by 72.22%.

关键词： Noise Information processing filtering algorithms Information filters Frequency response Pressure measurement Noise measurement Motion measurement MATLAB Motion artifacts

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Second-Order Newton-Based Extremum Seeking for Multivariable Static Maps

Second-Order Newton-Based Extremum Seeking for Multivariable...

引用

IEEE Conference on Decision and Control

作者： Azad Ghaffari Tiago Roux Oliveira School of Engineering and Computing Christopher Newport University Newport News VA USA Dept. of Electronics and Telecommunication Engineering State University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

A second-order Newton-based extremum seeking (SONES) algorithm is presented to estimate directional inflection points for multivariable static maps. The design extends the first-order Newton-based extremum seeking algorithm that drives the system toward its peak point. This work provides perturbation matrices to estimate the second- and third-order derivatives necessary for implementing the SONES. A set of conditions are provided for the probing frequencies that ensure accurate estimation of the derivatives. A differential Riccati filter calculates the inverse of the third-order derivative. The local stability of the new algorithm is proven for general multivariable static maps using averaging analysis. The proposed algorithm ensures uniform convergence toward directional inflection points without requiring information about the curvature of the map and its gradient. Simulation results show the effectiveness of the proposed algorithm.

关键词： Accuracy Level set Heuristic algorithms Estimation Low-pass filters filtering algorithms Cost function Frequency estimation Trajectory Convergence

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Video compression at extremely low bit rates

Video compression at extremely low bit rates

引用

Chinese Control and Decision Conference, CCDC

作者： Tianhao Wang Yi Fang Jian Wang Tong Gan Jun Xu Qiang Ling Department of Automation University of Science and Technology of China Hefei China Research and Development Anhui ShineAuto Autonomous Driving Technology Co. Ltd. Hefei China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Traditional video compression standards include AVC, HEVC, VVC, and AVS. These algorithms may result in ringing and blocking artifacts at extremely low bit rates, which can seriously affect video transmission quality. To address these issues, we propose a novel video compression method that combines super-resolution technology with traditional compression standards. In the encoder, we first down-sample the high-resolution input video and then use the HEVC algorithm to encode the low-resolution video into a bitstream. In the decoder, the HEVC algorithm decodes the received bitstream and inputs it into a super-resolution network to reconstruct the original high-resolution video. On the one hand, transmitting low-resolution video can reduce the required bandwidth, effectively mitigating the impact of ringing and blocking artifacts at extremely low bit rates. On the other hand, super-resolution technology can filter out ringing and blocking artifacts during the process of restoring high-resolution video. The experimental results show that our proposed method can achieve a better PSNR performance than the traditional HEVC algorithm on the standard HEVC Dataset.

关键词： Measurement Image coding Bit rate Superresolution Bandwidth Video compression filtering algorithms

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Neural Network-Based Hybrid Recommendation System

Neural Network-Based Hybrid Recommendation System

引用

Emerging Technology (INCET), International Conference for

作者： Bhuvan Singh Mangat Sahil K. Shah Vidya Kumbhar T.P. Singh Symbiosis Institute of Geoinformatics Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798350361155

ISBN: (纸本)9798350361162

The main goal of this study is to improve the user experience by providing personalized product recommendations based on user preferences and behaviors. The study examines the various methods and frameworks commonly used in e-commerce recommendation processes, including collaborative filtering, content filtering, and using these methods in neural networks system. Additionally, the proposed algorithm solves the “cold start problem” by newly visited users. Results obtained by proposed approach that use popularity-based algorithm to create the initial set of recommendations highlights how effective the system is at providing accurate and relevant recommendations to users, ultimately increasing customer satisfaction and sales conversion rates of supply. These findings and insights contribute to the development of e-commerce recommendation systems, and present possible avenues for future research and development.

关键词： filtering Collaborative filtering Neural networks filtering algorithms User interfaces User experience Electronic commerce

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An event-triggered distributed consensus information filter for target tracking in sensor networks

An event-triggered distributed consensus information filter ...

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Iranian Conference on Electrical Engineering (ICEE)

作者： Sara Giyani Behrouz Safarinejadian Sajad Shamsi Department of Electrical Engineering Shiraz University of Technology Shiraz Iran

ISBN: (数字)9798350376340

ISBN: (纸本)9798350376357

In this article, a distributed consensus information filter for sensor networks under the event-triggered strategy for tracking a target is proposed. According to this strategy in which the sensors only share their information with their neighbors at certain times, they can track their respective targets using the collected information. In addition, the event-trigger strategy is considered in order to reduce the required communication and an information gain matrix and an optimal distributed filter are created. Finally, a simulation example is presented to verify the effectiveness of the proposed algorithm.

关键词： Electrical engineering Estimation error Target tracking Heuristic algorithms filtering algorithms Information filters Complexity theory

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