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检索条件"主题词=Signal Processing Algorithms"

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Constrained Linear Model Predictive Control for an Artificial Pancreas

Constrained Linear Model Predictive Control for an Artificia...

引用

International Conference on Image and signal processing and their Applications (ISPA)

作者： Khadidja Fellah Arbi Mohamed Razi Morakchi Zineb Aziza El Aouaber Faycal Saffih Mohammed Sobir Djaddoudi Mohammed Bouregaa Sofiane Soulimane Biomedical Engineering Laboratory University of Tlemcen Algeria Laboratoire de Moivre Université de Sherbrooke Sherbrooke Canada Electrical and Electronics Engineering Department Istanbul Gelisim University Türkiye

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

The achievement of closed-loop glycemic control, and hence the automation of insulin administration, is highly required in the implementation of an Artificial Pancreas system. Various control theory approaches have been employed in numerous attempts to design an appropriate control algorithm. In our study, we adopted a Constrained linear model predictive controller (CLMPC). Our simulations have shown that the Constrained LMPC algorithm performs exceptionally well in maintaining blood glucose levels for patients across different scenarios. It effectively manages measurement and process noise, which is crucial for the practical implementation of the system. Moreover, the incorporation of feedforward capability in the controller has shown significant benefits, enabling proactive planning for future meals and optimizing blood glucose levels. Our CLMPC is more effective and very simple than the one presented in the literature, making it suitable for simple smartphone applications that support diabetes self-management.

关键词： Noise signal processing algorithms Predictive models Prediction algorithms Glucose Planning Pancreas

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Robust Point Tracking Based On Image Matching And Machine Learning On Video Images Taken from Fast Moving Camera

Robust Point Tracking Based On Image Matching And Machine Le...

引用

IEEE signal processing and Communications Applications (SIU)

作者： Ali Güven İmam Şamil Yetik Elektrik ve Elektronik Mühendisliği Bölümü TOBB Ekonomi ve Teknoloji Üniversitesi Ankara

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

Recently, providing real-time navigation of unmanned aerial vehicles independent of global positioning systems has become of great importance. The state-of-the-art methods based on deep learning, which give good results in certain datasets, and the existing methods can not provide real-time and good solutions on images with dynamic and fast moving. Moreover, the methods, were developed so far, were focused on object-based tracking algorithms. In this paper, the tracking of the points belonging to the target pattern, found by image matching, was performed with the machine learning model we developed for 10 sequential video images. The features extracted for the machine learning model are: (i) the change between the points of the previous image and the image before that, (ii) the points of interest in the previous image, (iii) the changes found with the homography matrix between sequential images. It was experimentally shown that, point tracking can be achieved with the least error, on avarage about 23 pixels for a 2 mega-pixel resolution image, among the algorithms in the literature that can process more than 30 images per second in a CPU environment of 2 GHz or above.

关键词： Target tracking Machine learning algorithms Image resolution Navigation Image matching signal processing algorithms Feature extraction

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EXTENSION FOR HANDWRITTEN CHARACTER RECOGNITION USING RNN-GRU ALGORITHM

EXTENSION FOR HANDWRITTEN CHARACTER RECOGNITION USING RNN-GR...

引用

signal processing, Computation, Electronics, Power and Telecommunication (IConSCEPT), International Conference on

作者： VS Moulishwar P Karthikevan V Mahendra Kumar A Srihariharan Department of Computer science and Engineering Sri Manakula Vinayagar Engineering College Puducherry India

ISBN: (数字)9798331540685

ISBN: (纸本)9798331540692

Recognizing handwritten characters is a complex task in pattern recognition and computer vision, demanding advanced techniques to enable computers to discern and transform handwritten or printed characters into a digital format. The integration of the GRU algorithm within the RNN-CNN hybrid methodology marks a significant advancement in handwritten character recognition. By transitioning from a character-by-character to a line-by-line recognition approach, the system aims to improve the conversion of handwritten text into digital formats. GRU enhances context awareness by predicting subsequent letters in incomplete words, thereby facilitating more accurate recognition. Leveraging the IAM dataset not only provides ample training data but also aids in error detection and correction, enhancing the overall accuracy and reliability of the system. This innovative approach underscores a commitment to advancing OCR capabilities beyond isolated characters and words, toward more comprehensive and context-aware text recognition, thereby paving the way for more effective digitization of handwritten documents.

关键词： Handwriting recognition Accuracy Text recognition signal processing algorithms Training data Transforms signal processing

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Image Super-Resolution Reconstruction Based on Holistic Attention Dual Regression

Image Super-Resolution Reconstruction Based on Holistic Atte...

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

作者： JunChen Liu Yuan You TianYou Zhang ShiYu Li School of Information Science and Engineering Shenyang Ligong University Shenyang China College of Foreign Studies Liaoning University Shenyang China North Huajin Chemical Industries Group Corporation Panjin China State Grid Corporation of China Huludao China

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

When addressing the challenges of an excessively large solution space and the difficulties in channel attention mechanisms to restore texture details during the generation of High-Resolution (HR) images from Low-Resolution (LR) images, an image super-resolution reconstruction algorithm based on the Holistic Residual Attention Dual Network (HRADN) is proposed. The use of a Dual Regression Network (DRN) with additional mappings is employed to estimate the downsampling kernel and impose constraints on the LR images, thereby reducing the solution space of functions. The incorporation of the Layer Attention Module (LAM) and Channel-Spatial Attention Module (CSAM) explores the correlations between different modules in the network and uncovers deeper information within the training data. Experimental evaluations conducted on five benchmark datasets have shown that the proposed algorithm outperforms several prevalent models in terms of Peak signal-to-Noise Ratio (PSNR), indicating its superior performance in super-resolution reconstruction. It significantly improves the clarity of details and reconstructs sharper high-frequency textures in subjective visual effects.

关键词： PSNR Attention mechanisms Superresolution signal processing algorithms Training data Reconstruction algorithms Visual effects Image reconstruction Standards signal resolution

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A Review of Converters Embedded with Impedance Measurement of Li-ion Battery

A Review of Converters Embedded with Impedance Measurement o...

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International Conference on Harmonics and Quality of Power

作者： Guangyang Chen Wenchao Liu Songlei Wang Kun Yang Zhengxiang Song Jinhao Meng School of Electrical Engineering Xi’an Jiaotong University Xi’an China

ISBN: (数字)9798350382563

ISBN: (纸本)9798350382570

Electrochemical impedance spectroscopy (EIS) has been concerned increasingly due to its relationship with inner states of batteries, which has underlying possibility to be deployed in battery management systems (BMSs). However, the traditional impedance measurements of batteries are constrained in the laboratory condition. The urgent requirement is exploring a practicable and applicable measuring system of battery impedance having the following features: time-saving waveform of excitation, signal generating device with merits of low-cost, low energy consumption and space-saving, and high accuracy signal processing algorithm. For this demand, a lot of researches have been done from the views of signal with impedance extraction and excitation device, and the most promising application is converters embedded with EIS measurement. Literatures related were summarized and analyzed in hope that providing a new perspective and inspiration for developing a feasible measuring system.

关键词： Energy loss Impedance measurement Reviews signal processing algorithms Modulation Battery charge measurement Time measurement Batteries Topology Impedance

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A weighted least squares approach for phase retrieval based on patch-wise noise level estimation

A weighted least squares approach for phase retrieval based ...

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Intelligent Control, Measurement and signal processing and Intelligent Oil Field (ICMSP), International Conference on

作者： Mingfeng Wang Yi Qin Dongguan University of Technology Dongguan China

ISBN: (数字)9798331516550

ISBN: (纸本)9798331516567

Phase measurement profilometry (PMP) is used in a wide range of 3D optical metrology applications. It is highly resistant to ambient light and object albedo, but it can be more prone to sensor and environmental noise. In this study, we present a novel approach for retrieving phase from noisy fringe patterns. Our method is based on weighted least squares (WLS) and noise estimation techniques. Firstly, we divide the noisy fringe patterns into overlapping patches. Then, we apply principal component analysis (PCA) to the patches, which allows us to effectively estimate the noise level and weight. We analyze the weight estimation and phase retrieval capability of our method concerning modulation, shift step, frequency, and size of the fringe pattern. We also provide simulation and experimental results to demonstrate the practical applicability of our proposed method.

关键词： Resistance Phase measurement Three-dimensional displays Working environment noise Estimation signal processing algorithms Probabilistic logic Noise measurement Noise level Principal component analysis

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Optimized Feature Selection Framework for Efficient Heart Sound Classification

Optimized Feature Selection Framework for Efficient Heart So...

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Delhi Section Conference (DELCON), IEEE

作者： Najeeba Ansari Musheer Ahmad Ishfaq Ahmad Khaja Mohammad Faraz Idris Siddiqui Department of Computer Engineering Jamia Millia Islamia New Delhi India

ISBN: (数字)9798331518592

ISBN: (纸本)9798331518608

Global data from the WHO indicates that cardiovascular illnesses are the world's biggest cause of mortality. The complexity of the heart's sound data and its dynamic features across time and frequency domains make the classification tasks difficult. Phonocardiograms (PCG) are very useful for assessing heart health and taking the required actions for early heart disease detection and prevention. In this paper, signal processing algorithms extract spatial and frequency features from PCG recordings and fuse them to create a generic feature vector. Further, optimized feature selection through genetic algorithm is done to reduce the dimensions and achieve the most relevant feature set. Finally, several machine learning algorithms are being examined to categorize heart sounds for both binary and multiclass classifications. The proposed framework attains performance accuracy of 91.22% for multiclass (3-class) and 93.92% for binary classification using CatBoost with GA feature selection. The performance is compared with many recent related methods to corroborate the proficiency of the proposed model over them.

关键词： Heart Support vector machines Radio frequency signal processing algorithms Feature extraction Vectors Recording Phonocardiography Remote monitoring Genetic algorithms

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Energy-Efficient Spectrum Sharing for Cellular V2X Communications

Energy-Efficient Spectrum Sharing for Cellular V2X Communica...

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International Conference on Wireless Communications and signal processing (WCSP)

作者： Yuxin Zhu Lin Zhu Wenqi Yang Yi Gong Junhui Zhao School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Jiangxi College of Construction Nanchang China Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

Increasingly scarce spectrum resources prompt spectrum sharing to be quite a potential solution to improve efficiency in the scenario of cellular vehicle-to-everything (CV2X), yet the respective quality of service (QoS) of different kinds of communication links should not be overlooked or confused. Besides, in response to the demand for green communication, the energy efficiency (EE) at the system level should be taken into consideration. Therefore, an energy-efficient spectrum sharing scheme with controllable interference is proposed in this paper, focusing on reusing spectrum between two typical technologies with different QoS requirements in C-V2X, more specifically, vehicle-to-infrastructure (V2I) with required capacity and vehicle-to-vehicle (V2V) with specific reliability. As an algorithm to achieve the optimal solution by imitating the natural evolution, a modified genetic algorithm (GA) with infeasible solution repairing is adopted to maximize the system EE thanks to its capability to cope with complex problems and reach the global optimal solution. Simulation results show that GA obtains a satisfactory convergence and the proposed spectrum sharing scheme effectively promotes the system EE.

关键词： Wireless communication Simulation signal processing algorithms Vehicular ad hoc networks Quality of service Interference Energy efficiency Optimization Genetic algorithms Convergence

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Optimizing Economic Load Dispatch problem Using Curve Fitting and Artificial Neural Networks

Optimizing Economic Load Dispatch problem Using Curve Fittin...

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Advances in signal processing, Power, Communication, and Computing (ASPCC), IEEE International Conference on

作者： Prajnadipta Sahoo Santi Behera Arun Kumar Sahoo Ajit Kumar Barisal Department of Electrical Engineering VSSUT Burla Odisha India Department of Electrical Engineering IIIT Bhubaneswar Odisha India Department of Electrical Engineering OUTR Bhubaneswar Odisha India

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

This paper introduces an innovative and efficient method for addressing the economic load dispatch (ELD) problem, leveraging curve fitting, artificial neural networks (ANN), and particle swarm optimization (PSO). ELD is a critical issue in power system management. Unlike static cost functions, realworld ELD problems involve variable costs due to factors such as coal quality, which complicates finding the global optimum with traditional mathematical methods. To tackle this, the paper employs curve fitting to determine the coefficients of the cost curves. These coefficients are then used to train an artificial neural network. The proposed algorithm’s effectiveness is demonstrated through extensive testing on a eight unit thermal generators. The approach accounts for variations in coal calorific values across different generators by integrating curve fitting, ANN, and PSO techniques. The results of the optimization are compared, showing significant improvements over existing methods.

关键词： Costs Power system management signal processing algorithms Artificial neural networks Coal signal processing Generators Curve fitting Particle swarm optimization Testing

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Control Strategies for 3L-T-Type Inverter in Islanded and Grid-Tied Modes Using Controller-Hardware in the Loop

Control Strategies for 3L-T-Type Inverter in Islanded and Gr...

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International Conference on Power Electronic Drives

作者： Dhiraj Kumar Yojan Sharma Aakash Singh Suvendu Samanta Department of Electrical Engineering Indian Institute of Technology Kanpur Uttar Pradesh India

ISBN: (数字)9798350372472

ISBN: (纸本)9798350372489

This paper presents the closed-loop control of a three-level T-type (3L-TNPC) inverter in both islanded and gridtied modes, with a focus on optimizing control strategies using a digital signal processor (DSP) microcontroller in conjunction with controller-hardware in the loop (C-HIL) through space vector pulse width modulation (SVPWM). The study leverages C-HIL to validate control algorithms in a realistic environment. It progresses to a comprehensive simulation phase in MATLAB/Simulink, utilizing proportional-integral (PI) control mechanisms to regulate the converter's operations. Furthermore, a 67 kVA power-rated inverter is evaluated through a C-HIL experimental setup in Typhoon HIL, an advanced real-time simulation platform. The performance of these methodologies is validated across various load types, both linear and nonlinear. The model is also tested in grid-tied mode, delivering 67 kVA of power to the grid at unity power factor (UPF). Additionally, total harmonic distortion (THD) is observed for both modes.

关键词： Space vector pulse width modulation Total harmonic distortion Tropical cyclones Microcontrollers Digital signal processors signal processing algorithms Inverters Real-time systems Mathematical models Load modeling

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