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检索条件"主题词=Filtering algorithms"

共 10368 条记录，以下是1441-1450 订阅

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Digital FIR Filter Design Using the Adaptive Window Function for Avian Acoustic Spotlighting

Digital FIR Filter Design Using the Adaptive Window Function...

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IEEE Control and System Graduate Research Colloquium (ICSGRC)

作者： Nemilyn A. Fadchar Jennifer C. dela Cruz College of Engineering and Information Technology Cavite State University Cavite Philippines School of Electrical and Electronics Engineering Mapua University Manila Philippines

ISBN: (数字)9798350386554

ISBN: (纸本)9798350386561

Biodiversity management is essential for preserving Earth's array of life, with birds playing a crucial role as indicators of environmental well-being. Avian acoustics has emerged as a valuable tool for assessing ecosystem health, forest degradation, and climate change. However, traditional bird survey methods are often invasive and time-intensive. Existing non-invasive techniques such as the deployment of passive acoustic and autonomous recorders encounter challenges such as high background noise, which can lead to misinterpretations. Digital filters are vital for processing acoustic signals particularly Finite Impulse Response (FIR) filters by reducing noise and limiting bandwidth. Yet, conventional FIR filter designs have limitations, especially regarding fixed window functions. This study proposed an innovative approach by employing an adaptive window function in FIR filter design using the Enhanced Cuckoo Search Optimization (ECSO) algorithm. This method dynamically adjusts the window function to balance main lobe width and sidelobe attenuation, thereby enhancing filter performance. The results of the simulation revealed that the proposed filter model achieved better filter characteristics and performance in terms of SNR, THD, and MSE. Likewise, the experimental setup, which involved testing the prototype in a natural habitat, showed that the avian acoustic spotlighting device successfully detected the intended bird vocalizations compared to other recording devices. Furthermore, its adaptable methodologies hold promise for addressing various signal processing needs beyond bioacoustics, thereby extending its impact and significantly contributing to ecological research and conservation efforts.

关键词： Performance evaluation Finite impulse response filters Heuristic algorithms Habitats Signal processing algorithms filtering algorithms Birds Acoustics Optimization Signal to noise ratio

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Research on Harmonic Detection Technology in Power Grids Based on Improved Phase-Locked Loop

Research on Harmonic Detection Technology in Power Grids Bas...

引用

Clean Energy Storage and Power Engineering (CESPE), International Conference on

作者： Xiaofeng Zhang Huisong Sun Department of Mechanical and Electrical Engineering Heilongjiang Institute of Construction Technology Harbin China

ISBN: (数字)9798331511708

ISBN: (纸本)9798331511715

With the large-scale integration of distributed generation into the power grid, issues such as frequency fluctuations, voltage imbalance, and harmonic distortion in power systems have become increasingly severe. Under such unbalanced and distorted grid conditions, the traditional $i_{p}-i_{q}$ harmonic detection method can no longer meet engineering requirements. Addressing problems such as harmonic distortion and DC components under non-ideal grid voltage conditions, an improved $i_{p}-i_{q}$ harmonic detection algorithm is proposed. This algorithm integrates an enhanced second-order generalized integrator (SOGI) filter into the conventional ip-iq harmonic detection loop. By doing so, it enhances the ability to filter out DC components and harmonics. Simulation results demonstrate that the improved phase-locked loop (PLL) can quickly lock onto the frequency under non-ideal grid voltage conditions, while effectively filtering out high-frequency signals and DC components. Furthermore, the current distortion rate detected using the new $i_{p}-i_{q}$ algorithm is significantly reduced.

关键词： Voltage fluctuations Simulation System performance filtering algorithms Harmonic analysis Real-time systems Harmonic distortion Smart grids Phase locked loops Power harmonic filters

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Implementation of Unscented Kalman Filter and Complementary Filter Applied to the ASSE scheme for Synthetic Flow Angles Estimation

Implementation of Unscented Kalman Filter and Complementary ...

引用

Conference on Digital Avionics Systems (DASC)

作者： Luca De Pasquale Gabriele Tarascio Angelo Lerro Piero Gili Department of Mechanical and Aerospace Engineering Polytechnic University of Turin Turin Italy

ISBN: (数字)9798350349610

ISBN: (纸本)9798350349627

This paper presents the results of the implementation of a quaternion-based Unscented Kalman Filter (UKF) and a Complementary Filter (CF), for attitude estimation, along with the Angle of Attack and Sideslip Estimator technology (ASSE), in order to provide an Air Data Synthetic Sensor for aerodynamic angles estimation. The attitude estimation is crucial for the computation of the full rotation matrix from the Inertial Reference Frame to the Body Reference Frame, needed by the ASSE algorithm. The estimation at issue exploits an Inertial Measurement Unit (IMU) equipped with a three-axis accelerometer, a gyroscope, a magnetometer and a Global Positioning System (GPS) receiver. Firstly, the filter algorithm is implemented in MATLAB and Simulink environment and its performance is assessed by using the measurements of a Flight Test Instrumentation (FTI) unit, a technological demonstrator built in Polytechnic University of Turin which encompasses the IMU. The verification is carried out with a series of tests employing a motion table at the National Metrology Institute of Italy (INRiM). Finally, the implementation of the filter with the ASSE technology is successfully demonstrated through a set of flight simulation data.

关键词： Estimation error Magnetometers Magnetic separation Receivers Aerospace simulation filtering algorithms Aerodynamics Gyroscopes Kalman filters Global Positioning System

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Precise Timescale for Research Advancements

Precise Timescale for Research Advancements

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European Frequency and Time Forum (EFTF)

作者： Jahnvi Verma August Connors Nischal Bhattarai Charles Rasor Thejesh Bandi Department of Physics and Astronomy Tuscaloosa USA

ISBN: (数字)9798350354270

ISBN: (纸本)9798350354287

We report the development and testing of the three different Kalman filter based algorithms for a new timescale at the University of Alabama (UA), with a vision for utilizing this as a unique test-bed for the timescale and time transfer research advancements for the future precise timekeeping. The Outlier Robust Kalman Filter (ORKF) has been implemented and tested in a timescale for the first time. A successful demonstration and characterization of different Kalman filters and weighting algorithms using three cesium clocks and one active hydrogen maser (AHM) is reported. Our timescale will have additional two AHMs in future making it a robust platform for algorithms testing geared towards the neural network methods.

关键词： Time-frequency analysis Neural networks Hydrogen Masers Europe filtering algorithms Kalman filters Frequency synchronization Testing Clocks

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BeliefTrack: A New Framework for Improving SORT-Like Tracking algorithms with Multi-Feature Association and Confidence Management

BeliefTrack: A New Framework for Improving SORT-Like Trackin...

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International Conference on Intelligent Transportation

作者： Wei Xu Dominique Gruyer Sio-Song Ieng COSYS PICS-L Université Gustave Eiffel Marne-la-Vallee France STIC Université Paris-Saclay Gif-Sur-Yvette France COSYS PICS-L Universite Gustave Eiffel Mame-la-Vallee France

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

DeepSORT [1], a widely recognized Kalman filter-based tracking-by-detection (KFTBD) algorithm, has inspired various derivative versions, named SORT-like algorithms in this paper. Building on our previous work and SORT-like algorithms, this paper introduces an innovative framework that integrates a multi-feature association based on belief theory, and several enhanced components based on confidence, such as the Kalman filter introducing associations confidence, which aims to improve tracking performance in various complex environments. The proposed method is designed to be generic and can be integrated into a SORT-like tracker for improvement. The performance and compatibility of the new framework, namely BeliefTrack, have been evaluated and validated by 1) applying it to several datasets containing various and complex environments, 2) comparing it to DeepSORT as the baseline and several variants versions from StrongSORT [2], and 3) adapting it to different detectors. In all cases, our BeliefTrack demonstrates improved results, sometimes significantly.

关键词： Uncertainty Buildings Detectors filtering algorithms filtering theory Kalman filters Intelligent transportation systems

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Correlation of High Harmonic Distortion to Shunt Active Power Filter Operation and Performance

Correlation of High Harmonic Distortion to Shunt Active Powe...

引用

IEEE Symposium on Industrial Electronics & Applications (ISIEA)

作者： NFA Abdul Rahman AA Hairunizam School of Electrical Engineering College of Engineering Universiti Teknologi MARA Shah Alam Malaysia

ISBN: (数字)9798350386868

ISBN: (纸本)9798350386875

Nonlinear load proliferation in power systems distorts the grid supply current and increases the Total Harmonic Distortion (THD) value. Therefore, this research investigates harmonic components produced by capacitive and inductive nonlinear loads. Next, it focuses on the effect of those harmonic components in selecting a single-phase Shunt Active Power Filter's (SAPF) DC-link voltage. Later, it assesses the filter performance using two DC-link voltage control algorithms tuned under two different operating conditions. In this research, the resistive value of both nonlinear loads is adjusted to ensure the load currents consist of the same fundamental component. Initially, a DC source is connected in parallel with the DC-link capacitor to remove the need for a Voltage Control Algorithm (VCA). Later, the VCA is tuned under two operating conditions when the DC source is removed from the filter. The simulation results verify that the load current of the capacitive nonlinear load has a higher THD value than the inductive nonlinear load; there is a significant difference in the amplitude of the harmonic components at low frequencies. Furthermore, the findings show that the SAPF requires a higher DC-link voltage when compensating for current with a higher THD value. It also verifies that VCA should be tuned under extreme harmonic distortion to enhance the SAPF versatility. All results demonstrate that nonlinear loads significantly affect the SAPF operation and performance.

关键词： Power filters Total harmonic distortion Reactive power Correlation Simulation filtering algorithms Active filters

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Research on Ubiquitous Power Internet of Things in Distribution Networks Using Adaptive Gradient Algorithm with Convolution Neural Network

Research on Ubiquitous Power Internet of Things in Distribut...

引用

Data Science and Network Security (ICDSNS), International Conference on

作者： Songmei Liu Wanjiang University of Technology Ma'anshan China

ISBN: (数字)9798350373110

ISBN: (纸本)9798350373127

In China, several distribution automation devices are established in distribution network to increase reliability of power supply. The major challenge of ubiquitous electric Internet of Things (IoT) is a resource aspect which enables distributed computational sources. Therefore, the Adaptive Gradient Algorithm with Convolution Neural Network (Adagrad-CNN) is proposed for ubiquitous electric IoT in distribution networks. The Adagrad is helpful when dealing with sparse features or data that has extensive-range of values. The CNN has multiple-layer architecture for classifying image pixels patterns through processing and it filtered noise captures significant predictive properties. The Adagrad-CNN leads to better generalization and enhance the CNN performance through mitigating issues based on exploding gradients that is essential when dealing with difficult and large datasets in ubiquitous electric IoT. The dataset is collected from various devices and sensors in the power grid and it is preprocessed by Z-score normalization. This preprocessing enhances convergence rates and reduces the large scales. It is essential when features are in different ranges and it prevents particular feature dominance. The Adagrad-CNN attains 96.54%, 94.21 %, 95.73% and 94.59% of accuracy, recall, precision and f1-score.

关键词： Performance evaluation Adaptive systems Neural networks Noise Distribution networks filtering algorithms Prediction algorithms Power grids Sensors Internet of Things

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Adam Pine cone optimization with Deep learning for cervical cancer detection using pap smear image

Adam Pine cone optimization with Deep learning for cervical ...

引用

Intelligent Technologies (ACOIT), Asian Conference on

作者： V T Ram Pavan Kumar P.L. Ramesh M Arulselvi Department of MCA K.B.N College Vijayawada Andhra Pradesh Department of Computers K.B.N College Vijayawada Andhra Pradesh Department of CSE Annamalai University Chidambaram Tamil Nadu

ISBN: (数字)9798350374957

ISBN: (纸本)9798350374964

Cervical cancer is the main reason of mortality in females worldwide. The Human Papillomavirus (HPV) is the major reasonfor cervical cancer in female patients. The virus first infects cells in the cervix of female patients and spreads throughout the cervix. This cancer is curable if diagnosed early and treated on time. Here, this paper presents an innovative method based on Deep Learning (DL) for detecting cervical cancer. Initially, the input pap smear image is considered as inputand is forwarded to the preprocessing step in which the noise contained in the pap smear image is eradicated utilizing an adaptive bilateral filter. Next, Utilizing a Mask Regional Convolutional Neural Network (Mask-RCNN) the affected region is segmented and shape features are mined from the segmented image. Then, cervical cancer detection is effectuated by exploiting the Deep Maxout Network (DMN) model, which is structurally optimizedbythe designed Adam Pine Cone Optimization Algorithm (APCOA). Furthermore, the performance of APCOA_DMN is assessed using several metrics and it obtained anaccuracyof $\mathrm{9 1. 2 8 4 \%}$, a True Negative Rate (TNR) of $91.315 \%$, and a True Positive Rate (TPR) of $\mathrm{9 1. 9 7 9 \%}$.

关键词： Measurement Deep learning Image segmentation Accuracy Noise Adaptive filters Mortality filtering algorithms Cervical cancer Optimization

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Research of mask wearing detection method using Improved YOLO network

Research of mask wearing detection method using Improved YOL...

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Chinese Control and Decision Conference, CCDC

作者： Fei Xiao Zixi Liu Shengbin Zhao Shuai Yuan School of Computer Science and Engineering Shenyang Jianzhu University Shenyang China Daqing Oilfield Limited Company DaQing China School of Computer Science and Engineering Shenyang Jianzhu University Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction Shenyang Branch of National Special Computer Engineering Technology Research Center Shenyang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Mask wearing detection technology is a practical and research-oriented area within object detection. Due to the complexity of mask wearing detection scenarios, issues such as small target detection and low image clarity often result in missed detections and false alarms. The YOLO algorithm, known for its fast detection speed, is commonly used in mask wearing detection. However, the original YOLO algorithm struggles to achieve satisfactory results in dense crowd scenarios. Therefore, this paper proposes an improved YOLOv5 algorithm based on the BiFPN structure and incorporating attention mechanisms to enhance the accuracy of mask wearing detection while maintaining real-time performance. The proposed approach firstly introduces the Bidirectional Feature Pyramid (BiFPN) structure into the backbone network to enhance the feature extraction capability. Additionally, attention mechanisms are incorporated to filter out irrelevant information, conserve computational resources, and improve the detection performance for small targets. Experimental results on a custom dataset demonstrate that the YOLOv5_BiFPN algorithm achieves a 4% improvement in accuracy and an 11.7% increase in mAP50 compared to the original YOLOv5. Moreover, the inclusion of attention mechanisms further boosts the accuracy by an additional 1.6%. These findings confirm that the improved YOLOv5s model exhibits superior performance in the task of mask wearing detection.

关键词： YOLO Attention mechanisms Accuracy filtering algorithms Feature extraction Information filters Real-time systems

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Multimodal Analysis of Bone Mineral Density Classification

Multimodal Analysis of Bone Mineral Density Classification

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International Conference on Biosignals, Images and Instrumentation (ICBSII)

作者： K. Sneha C. Sridevi B. Yazhini Amridha Lakshmi Venkkautaesh Department of Electronics and Communication Engineering Madras Institute of Technology Chennai India

ISBN: (数字)9798350350951

ISBN: (纸本)9798350350968

Osteoporosis is a skeletal disorder marked by diminished bone mineral density and mass, impacting bone health, mass, or alterations in bone structure and strength. This decline in bone strength heightens the susceptibility to fractures. Notably, osteoporosis is often asymptomatic, making it a "silent" ailment. The assessment of deficiencies in joint images is a prolonged procedure conducted manually, demanding the expertise of professionals to periodically analyze the scans. This manual approach results in time delays and heightened costs. To address this issue efficiently, this work aims to pinpoint bone mineral density, a crucial factor in identifying bone-related diseases and assessing the risk of fractures in an automated fashion by comparing Dual Energy X-ray Absorptiometry and X-ray images. The workflow is initiated with image pre-processing followed by Image enhancement, Data Augmentation, Data partition, feature extraction and classification. The images are enhanced using a median filter, normalization techniques and CLAHE - Contrast Limited adaptive histogram equalization algorithm. VGG-16, ResNet, DenseNet, InceptionV3 and Inception-ResNet are the different transfer learning models employed in this work to analyze and extract the best algorithm that provides the desired results.

关键词： Osteoporosis Histograms Accuracy Density measurement filtering algorithms Feature extraction Bone density

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