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检索条件"主题词=filtering algorithms"

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Enhancing the Optimization Efficiency of Modal Filters Based on Microstrip Lines Using Regression Machine Learning Models

Enhancing the Optimization Efficiency of Modal Filters Based...

引用

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

作者： Georgiy Yu. Kim Anton O. Belousov Viktoriya O. Gordeyeva Television and Control Department Tomsk State University of Control Systems and Radioelectronics Tomsk Russian Federation

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

This work presents the first implementation of three machine learning models to enhance the optimization efficiency of a modal filter based on a three-conductor microstrip line. The training was conducted on a comprehensive dataset (including intermediate and final results) obtained from the optimization of the modal filter using a simple genetic algorithm aimed at minimizing the maximum output voltage of the modal filter (U max ). The machine learning models considered include random forest, gradient boosting, and ridge regression. A range of key metrics was employed to evaluate the quality of the trained models, providing a comprehensive analysis of their accuracy, reliability, and efficiency. In particular, the coefficient of determination (R 2 ), mean absolute error, and root mean square error were examined. A significant reduction in the time required to find optimal parameters was demonstrated (running a simple genetic algorithm with 5000 evaluations takes approximately 12,000 seconds) while maintaining the accuracy of the results obtained. Specifically, the performance of the three trained models on a separate dataset, not used during training, showed the ability to predict the value of U max at modal filter output with an accuracy of up to 1.75%, 0.77%, and 7.98% for the random forest, gradient boosting, and ridge regression models, respectively. A detailed analysis of the obtained results was performed, highlighting the advantages and limitations of the trained machine learning models in the design tasks of the modal filter.

关键词： Training Radio frequency Microstrip filters Adaptation models Accuracy Predictive models filtering algorithms Optimization Random forests Genetic algorithms

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Investigation of the Noise Immunity of Various Variants of the MMSE Algorithm when Implemented on a Fixed-Point Processor

Investigation of the Noise Immunity of Various Variants of t...

引用

Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO)

作者： Ben Rejeb Sofien Vitaly Kreyndelin Moscow Technical University of Communications and Informatics Moscow Russia

ISBN: (数字)9798350373448

ISBN: (纸本)9798350373455

The analysis of the noise immunity of two variants of the MMSE algorithm implementation was carried out on a fixed-point processor in this report. The first option is a matrix inversion using QR decomposition, and the second algorithm is implemented using a Kalman filter. Two variants of the algorithm behavior at the integer different lengths and fractional parts of the processor's number representation was considered. Noise immunity plots have been obtained for QAM-16 modulation method using a 4x4 antenna configuration. It is shown that for various integer lengths and fractional part of the representation of processor numbers, the MMSE algorithm, when implemented on a fixed-point processor and implemented using a Kalman filter, has higher noise immunity compared to the MMSE algorithm when implemented on a fixed-point processor and with matrix inversion using QR decomposition.

关键词： Noise Modulation filtering algorithms Telecommunications Kalman filters Matrix decomposition Synchronization

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Smart Recommendation System For Flourishing Gardens Using Deep Learning Techniques

Smart Recommendation System For Flourishing Gardens Using De...

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Advances in Computing, Communication and Networking (ICAC2N), International Conference on

作者： M. Meenalochini S. Kishore V. Sabarika S. Nandhakumar Department of CSD Kongu Engineering College Tamil Nadu India

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

Our project introduces a specialized model focusing on companion planting, specifically for the onion-carrot pair. It integrates advanced deep learning algorithms, including graph neural networks (GNNs), collaborative filtering, and content-based filtering. The model offers personalized companion plant recommendations based on user input and incorporates pest control and disease prediction functionalities tailored to selected plants. Through thorough data analysis and consideration of user preferences, the model provides customized suggestions to optimize plant growth and health, taking into account environmental factors such as climate conditions. Utilizing GNNs, the model enhances pest control by analyzing images to identify pests, while collaborative filtering refines pest management strategies based on similar contexts. For disease prediction, content-based filtering evaluates historical data and plant traits to forecast disease risks, facilitating proactive measures for plant health protection. By harnessing advanced deep learning techniques and tailored recommendations, this project aims to empower agricultural practitioners with actionable insights for sustainable gardening practices, enhancing crop productivity, and promoting environmental stewardship in agriculture.

关键词： Deep learning Productivity Analytical models filtering Collaborative filtering Pest control filtering algorithms Prediction algorithms Graph neural networks Diseases

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Optimal Reduced-order Filter for Systems with Deterministic Observations and Stochastic Observations

Optimal Reduced-order Filter for Systems with Deterministic ...

引用

Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Yuan Gao Shuli Sun School of Electronic Engineering Heilongjiang University Harbin China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

For linear discrete time-invariant systems with deterministic observations and random observations, the optimal reduced-order filtering problem is studied. Some of the state components can be obtained directly by deterministic observation, while others can be obtained by designing a reduced-order state filter. Compared with the method of augmenting the observation, it not only reduces the calculation burden, but also avoids the problem of numerical instability caused by the singular observation noise variance matrix. The method presented in this paper can solve the estimation problem of systems with state equality constraint and singular observation noise variance matrix. A simulation example verifies the effectiveness of algorithm.

关键词： filtering Noise Estimation filtering algorithms filtering theory

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Algorithm for the Multi-target Joint Detection and Ambiguity Resolving Based on Dynamic Programming

Algorithm for the Multi-target Joint Detection and Ambiguity...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Yitong Mao Chong Song Bingnan Wang Chenhao Zhao National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences China State Key Laboratory of Remote Sensing Science Aerospace Information Research Institute Chinese Academy of Sciences China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

The mode of wide range surveillance and over-sight detection of satellite platform brings serious range ambiguity. The traditional method is to transmit multiple Pulse Repetition Frequencies (PRFs) and correlate them to solve the ambiguity. To ensure the detection of targets by using low threshold, which will lead to a large number of false alarms. In order to solve this problem, a new algorithm for the multi-target joint detection and range ambiguity resolving based on dynamic programming algorithm (DP) is presented. The algorithm divides the false alarm suppression and deblurring into several sub-problems. By splitting into sub-sequences for association operations, and then the sub-results are associated to obtain the unambiguous target state prediction that suppresses false alarms. It effectively alleviates the problem of sudden increase in computational complexity caused by the multi-target, and has better real-time performance.

关键词： Satellites Heuristic algorithms Surveillance Estimation filtering algorithms Prediction algorithms Real-time systems

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Android Malware Detection using Fast Correlation Based Filter and Random Forest Algorithm

Android Malware Detection using Fast Correlation Based Filte...

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International Seminar on Application for Technology of Information and Communication (ISemantic)

作者： Sabrina Aska Amalina Fauzi Adi Rafrastara Muhammad Ibadullah Faculty of Computer Science Universitas Dian Nuswantoro Semarang Indonesia

ISBN: (数字)9798350366648

ISBN: (纸本)9798350366655

Malware analysts have faced several difficulties in the past few years due to the rapid growth of Android malware. This surge in Android malware not only threatens the security and privacy of users but also undermines the integrity of the Android ecosystem. As cybercriminals get more advanced, the methods for detecting and dealing with malware need to grow more sophisticated. To find the best combination for identifying Android malware, this study compares different machine learning algorithms and feature selection techniques. The dataset used in this research is the CICMaldroid2020 dataset. The results indicate that the combination of the Fast Correlation-Based Filter feature selection method and the Random Forest algorithm achieved the highest performance, with both accuracy and F1-Score at 92.5%.

关键词： Seminars Privacy Machine learning algorithms filtering algorithms Information filters Feature extraction Malware Security Surges Random forests

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Iterative Sparse Interference Cancellation Algorithm for Non-Stationary Massive MIMO Uplink System Based on ZF Filter

Iterative Sparse Interference Cancellation Algorithm for Non...

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International Conference on Information, Communication and Networks (ICICN)

作者： Guan Qingyang Wu Shuang College of Engineering Xi'an International University Xi'an China

ISBN: (数字)9798350355802

ISBN: (纸本)9798350355819

In this paper, we introduce the sparse interference cancellation scheme in non-stationary massive MIMO uplink systems. Due to the sparsity for non-stationary massive MIMO, we propose the multi-layer implementation method for constructing sparse interference cancellation algorithm, which consist of multiple layers including channel sparse estimation layer using an improved SAMP, sorting layer and filtering layer through comparing with noise power threshold. The theoretical proof of noise power threshold power is proved. By constructing sparse ZF filter, we also analyze its feasibility and robustness under different multi-user access conditions through simulation. Then, we proposed the iterative methods based on sparse ZF scheme to reduce the complexity. Symbols would be sequentially detected and eliminated interference from all other users at every iteration. We also provide an iteration termination condition based on the IC algorithm and provide the theoretical proof. Furthermore, we proposed preprocessing method based on channel power reordering. Analysis and simulation results show that under different milt-user access, the performance of our proposed sparse interference cancellation approach ideal MAP detection.

关键词： Interference cancellation Simulation Noise Estimation Massive MIMO filtering algorithms Robustness Complexity theory Uplink Sorting

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A Seven Tuple Firewall Rule Matching Algorithm Based on Hash Table

A Seven Tuple Firewall Rule Matching Algorithm Based on Hash...

引用

Asian Control Conference

作者： Yue Teng Zhuohan Li School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The traditional firewall packet filtering process primarily relies on five tuple firewall filtering rules for matching, encompassing the source IP address, destination IP, protocol type, source port, and destination port. However, due to the escalating sophistication of network attacks, the effectiveness of five tuple rules in safeguarding networks is constrained, thereby compromising the security of network communications. In this paper, a seven tuple firewall filtering rule is first proposed, which augments the existing five tuple by incorporating two additional elements: source Mac address and destination Mac address. Subsequently, a thorough analysis is conducted on potential conflicts among seven tuple firewall rules. Employing a divide and conquer strategy, the firewall rules are segmented into four subsets based on the network model: data link layer set, network layer set, transport and application layer set, and combined rule set. Furthermore, a method is proposed for achieving a conflict-free rule set by leveraging the relationships among the rules. Finally, a seven tuple firewall rule matching algorithm is introduced, which relies on a hash table built upon the conflict-free rule set. Compared to five tuple rules, seven tuple rules enable more targeted rule creation for specific devices within the network. Additionally, the algorithm outlined in this paper exhibits a straightforward data structure, facilitates easy rule updates, and boasts significantly faster matching speeds in comparison to traditional algorithms.

关键词： Matched filters Protocols Firewalls (computing) filtering filtering algorithms Data structures Data models

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Experimental Teaching of Digital PID Controllers

Experimental Teaching of Digital PID Controllers

引用

Technologies Applied to Electronics Teaching (TAEE)

作者： Santiago Tainta Ausejo Carlos A. de La Cruz Blas Jaime Cid Monjaraz Departamento de ingeniería eléctrica electrónica y comunicación Public University of Navarre Pamplona Spain Facultad de ciencias de la electrónica Benemerita Universidad Autonoma de Puebla Puebla Mexico

ISBN: (数字)9798350348675

ISBN: (纸本)9798350348682

PID controllers are a fundamental building block of industrial control systems. In this paper we present a simple demonstrator that can be assembled using basic electronic components and an Arduino UNO development board as plant and digital controller, respectively. The complete system can be easily built using components that are often available in a basic electronic lab, avoiding mechanical or electromechanical systems. The proposed system is open and flexible, allowing the study of digital PID control systems and the experimental evaluation of different tuning methods.

关键词： PI control Control engineering Education Process control Electronic components filtering algorithms PD control

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Research on Primary Frequency Regulation of Wind Power Integrated with Hybrid Energy Storage Based on Fuzzy Logic Control

Research on Primary Frequency Regulation of Wind Power Integ...

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Energy Storage and Conversion (ISESC), CPSS & IEEE International Symposium on

作者： Weiquan Wang Yuhang Ma Yilin Bai Kun Yang Zhengxiang Song State Key Laboratory of Electrical Insulation and Power Equipment Xi'an Jiaotong University Xi'an China School of future technology Xi'an Jiaotong University Xi'an China

ISBN: (数字)9798350380514

ISBN: (纸本)9798350380521

With growing wind-generated system in grids, frequency regulation pressure increases. Therefore, a control strategy aimed at primary frequency regulation is proposed in this paper, hybrid energy storage and wind power are coordinated in this strategy. Battery storage and flywheel storage together constitute hybrid energy storage. The filtering algorithm allocates frequency regulation power of two types energy storage. Fuzzy logic control determines the time constant of the filter function, taking into account the power and SOC of the battery and flywheel. Finally, a model of the wind-generated system and hybrid energy storage system is constructed and simulated. It is proved by the results that, according to the above strategy, primary frequency regulation can be achieved, resulting in higher frequency stability of the grid.

关键词： Fuzzy logic Wind power generation Power system stability filtering algorithms Hybrid power systems Stability analysis Batteries Flywheels State of charge Frequency control

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