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检索条件"主题词=Filtering algorithms"

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Optimizing Resource Allocation in Filterless Elastic Optical Networks over C+L Band: QoT-Aware Approach

Optimizing Resource Allocation in Filterless Elastic Optical...

引用

International Conference on Transparent Optical Networks

作者： Sadegh Ghasrizadeh Farhad Arpanaei Luis Velasco Hamzeh Beyranvand Optical Communications Group (GCO) Universitat Politècnica de Catalunya (UPC) Barcelona Spain Department of Telematic Engineering Universidad Carlos III de Madrid Madrid Spain Department of Electrical Engineering Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran

ISBN: (数字)9798350377323

ISBN: (纸本)9798350377330

Filterless optical networks (FONs) offer a cost-effective alternative to traditional networks by utilizing passive couplers/splitters. However, this approach leads to leakage signals and wasted spectrum. With the transition to elastic optical networks (EONs), which efficiently utilize spectrum, incorporating L-band alongside C-band offers expanded frequency resources. This paper proposes an approach to address quality of transmission (QoT)-aware tree selection, routing, modulation, and spectrum assignment (QTRMSA) in filterless EONs (FEONs) over C+L band. Heuristic algorithms are presented for complex large-scale networks, showing comparable performance in spectrum usage and modulation format. These algorithms highlight the impact of generalized signal-to-noise-ratio (GSNR) estimation methods on spectrum usage, blocking, and outage. Additionally, the proposed MX5 method ensures minimal outage or blocking up to a network throughput of $120 \mathrm{~Tb} / \mathrm{s}$ over $\mathrm{C}+\mathrm{L}$ band for large scale network (Telefonica region B network topology). These results provide insights for balancing performance metrics and optimizing resource allocation for FEONs over $\mathrm{C}+\mathrm{L}$ band transmission.

关键词： Optical filters Measurement Network topology Heuristic algorithms Optical fiber networks filtering algorithms Throughput

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Rolling Bearing Fault Diagnosis Method Based on Variational Modal Decomposition Envelope Spectrum

Rolling Bearing Fault Diagnosis Method Based on Variational ...

引用

Student Conference on Research and Development (SCOReD)

作者： Zhang Jingsong Yang Soo Siang Jing Zhe Zhou Xiaolong Tan Min Keng Wang Yanzhen Faculty of Engineering Universiti Malaysia Sabah Sabah Malaysia College of Mechanical Engineering Beihua University Jilin China

ISBN: (数字)9798331510077

ISBN: (纸本)9798331510084

Aiming at the problem that the early characteristics of rolling bearing faults are weak, and the traditional envelope spectrum analysis method lacks quantitative feature parameters, a fault diagnosis method based on variational modal decomposition (VMD) envelope spectrum is proposed. Firstly, the maximum correlation kurtosis deconvolution (MCKD) algorithm is used to denoise the rolling bearing fault signal to enhance the fault characteristic information of the signal. Secondly, VMD is used to decompose the filtered signal, and the selection method of the key parameters that affect the accuracy of the decomposition is deeply studied, and the relevant selection method is proposed. Finally, the intrinsic mode function (IMF) sensitive to fault information is selected based on the energy entropy increment-kurtosis criterion, and the amplitude feature ratio of the envelope spectrum and the envelope spectrum entropy are used to quantify the fault feature information of the sensitive IMF components. Construct a multi-feature high-dimensional state feature vector and use the fuzzy C-means (FCM) clustering method to classify and diagnose rolling bearing faults. Through the analysis of experimental data and measured data, the validity and universality of the proposed method are verified.

关键词： Fault diagnosis Accuracy Rolling bearings filtering algorithms Information filters Entropy Kurtosis Vectors Spectral analysis Research and development

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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...

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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...

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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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Controllable Privacy in Face Recognition: A Filter-based Approach

Controllable Privacy in Face Recognition: A Filter-based App...

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IEEE International Joint Conference on Biometrics (IJCB)

作者： Zohra Rezgui Nicola Strisciuglio Raymond Veldhuis University of Twente Enschede The Netherlands Norwegian University of Science and Technology Gjøvik Norway

ISBN: (数字)9798350364132

ISBN: (纸本)9798350364149

Recent advancements in deep learning for face recognition have led to concerns regarding privacy and algorithmic bias, particularly in inferring demographic attributes from facial templates. Existing methods often struggle to balance privacy preservation with utility and operational efficiency. In this paper, we propose a filter-based privacy-enhancing method inspired by the information bottleneck concept. Our approach involves training a filter estimator that assigns scores to intermediate-layer elements based on their sensitivity to target attributes. By selectively replacing sensitive elements with noise while allowing less sensitive ones to pass through, our method aims to enhance privacy while managing the trade-off with verification performance. Most importantly, our approach allows for post-training tuning of the privacy-utility trade-off, providing flexibility for different operational requirements. Evaluation across multiple face recognition networks and datasets demonstrates that our approach can achieve substantial gains in the gender obfuscation task while maintaining adequate verification performance and computational efficiency suitable for real-time applications.

关键词： Training Privacy Visualization Sensitivity Face recognition Noise filtering algorithms Information filters Real-time systems Tuning

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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...

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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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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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Experimental Teaching of Digital PID Controllers

Experimental Teaching of Digital PID Controllers

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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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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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$\chi^{2}$ Test Based Cubature Kalman Filter Algorithm and its Application in SINS Alignment

$\chi^{2}$ Test Based Cubature Kalman Filter Algorithm and i...

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Electrical Engineering and Automation (IFEEA), International Forum on

作者： Yacheng Liang Chun Yang Chen Qian Yang Gao Hefei Rail Transit Group Operation Co. Ltd Hefei China Nanjing Research Institute of Electronic Engineering Nanjing China School of Automation Nanjing University of Science and Technology Nanjing China

ISBN: (数字)9798331516611

ISBN: (纸本)9798331516628

Addressing the issue of abnormal measurements influencing the accuracy of navigation state filtering during the in-motion alignment process, a $\chi^{2}$ test based Cubature Kalman Filter (CTCKF) algorithm is proposed. This algorithm aims to enhance system robustness without increasing computational load. By leveraging the state estimates obtained from both the time prediction and measurement update steps in the cubature Kalman filtering process, and assuming that the difference between these two estimates follows a Gaussian distribution, a $\chi^{2}$ test function is established to examine the measurement information. Through the implementation of a constructed fuzzy membership function, the measurement noise in the filtering process is adaptively amplified, thereby mitigating the impact of abnormal measurements on state estimation. Simulation experiments with unmanned aerial vehicles demonstrate that the proposed the CTCKF algorithm enhances system robustness without imposing additional computational burden.

关键词： Accuracy filtering Noise filtering algorithms Prediction algorithms Time measurement Robustness Kalman filters Noise measurement State estimation

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