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检索条件"主题词=Software Algorithms"

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PWM algorithm for Dual three-phase PMSM driving system

PWM algorithm for Dual three-phase PMSM driving system

引用

International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Meng Luo Yuan Zhu Intron Technology(Shanghai) Co. Ltd. Shanghai China School of Automotive Studies Tongji University Shanghai China

ISBN: (纸本)9781665435253

In order to improve the efficiency of dual three-phase permanent magnet synchronous motor (DT-PMSM), a novel overmodulation algorithm is proposed. In non-sinusoidal voltage modulation area, based on the space vector pulse width modulation (SVPWM) algorithm, minimum amount of harmonic voltages injected in the harmonic subspace are calculated using improved four-vector space vectors. In order to simplify the PWM hardware and software implementation, the modulation algorithm is implemented with three-phase decomposition PWM, which can generate symmetric pulse width modulation waveforms. And it can transit from sinusoidal voltage modulation region to non-sinusoidal voltage modulation region smoothly. The effectiveness of the proposed algorithm has been validated in experimental in a Dual-three PMSM driving system. Keywords-Dual-three PMSM; overmodulation; four vectors SVPWM; three-phase decomposition PWM; harmonics suppression

关键词： Space vector pulse width modulation Harmonics suppression software algorithms Voltage Aerospace electronics Harmonic analysis Permanent magnet motors

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Swapping algorithm and meta-heuristic solutions for combinatorial optimization n-queens problem

Swapping algorithm and meta-heuristic solutions for combinat...

引用

Science and Information Conference (SAI)

作者： Neil Vaughan I. V. Prangidhvili Laboratory of Distributed Information-and-Analytical Control Systems V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences Moscow Russia

This research proposes the swapping algorithm a new algorithm for solving the n-queens problem, and provides data from experimental performance results of this new algorithm. A summary is also provided of various meta-heuristic approaches which have been used to solve the n-queens problem including neural networks, evolutionary algorithms, genetic programming, and recently Imperialist Competitive Algorithm (ICA). Currently the Cooperative PSO algorithm is the best algorithm in the literature for finding the first valid solution. Also the research looks into the effect of the number of hidden nodes and layers within neural networks and the effect on the time taken to find a solution. This paper proposes a new swapping algorithm which swaps the position of queens.

关键词： Algorithm design and analysis Genetic algorithms Optimization Neural networks Heuristic algorithms software algorithms Evolutionary computation

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Multichannel WOLA algorithm in hydroacoustic monitoring tasks and its computer simulation in MATLAB

Multichannel WOLA algorithm in hydroacoustic monitoring task...

引用

International Conference on Computer Technologies in Physical and Engineering Applications

作者： Dmitry I. Kaplun Dmitry M. Klionskiy Alexander S. Voznesenskiy Vyacheslav V. Gulvanskiy Electrotechnical University LETI Saint Petersburg Russia

The paper presents a multichannel weighted overlap-add (WOLA) algorithm applied to sub-band signal processing in hydroacoustic monitoring tasks. WOLA is illustrated as a multichannel filter bank implementation in terms of block-by-block signal analysis using vector discrete Fourier transform. software implementation in MATLAB is discussed and the computation times are provided.

关键词： Discrete Fourier transforms Vectors Signal processing algorithms Monitoring MATLAB Algorithm design and analysis software algorithms

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Algorithm for Ranking News

Algorithm for Ranking News

引用

International Conference on Semantics, Knowledge and Grid (SKG)

作者： Xiaofeng Liu Chuanbo Chen YunSheng Liu Huazhong Univ. of Sci. & Technol. Wuhan

With the overwhelming volume of online news available today, there is an increasing need for efficient technique to satisfy user news need. In this paper, news ranking is discussed and news informational retrieval model is presented for novel news ranking algorithm. In terms of examination of properties of news articles produced by news ranking function, semantic relevancy, freshness, citation count and degree of authority are combined into the model, and extended relevance is proposed. The basic idea is that the relevance between news article and user news need is determined by semantic relevance, freshness, citation count and degree of authority of news article. The experimental results show that new model and algorithm have higher precision and produce more relevant results than traditional vector retrieval model.

关键词： Search engines Web pages HTML Information retrieval Internet software algorithms software engineering Clustering algorithms TV broadcasting

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The classification algorithm development of photomasks defects based on fuzzy logic

The classification algorithm development of photomasks defec...

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IEEE International Conference on Data Stream Mining & Processing (DSMP)

作者： Yuliya Kozina Nataliya Gulyaeva Odesa National Polytechnic University Odesa Ukraine

ISBN: (纸本)9781509037377

In modern conditions of microelectronic products manufacture the automated control of photomasks quality is an important problem. It execution on the basis of the proposed the intellectual quality control system of photomasks allowed to select and classify defects. Using of fuzzy logic in the algorithm development of photomasks defects classification is allowed to increase of classification reliability.

关键词： Fuzzy logic Classification algorithms Quality control software algorithms Reliability Production Libraries

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Implementation of Hyperparameter Tuning Random Forest Algorithm in Machine Learning for SDN Security: An Innovative Exploration of DDoS Attack Detection

Implementation of Hyperparameter Tuning Random Forest Algori...

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Artificial Intelligence, Blockchain, Cloud Computing, and Data Analytics (ICoABCD), International Conference on

作者： Hijrah Nisya Sofia Naning Hertiana Yudha Purwanto School of Electrical Engineering Telkom University Bandung Indonesia

ISBN: (数字)9798350368451

ISBN: (纸本)9798350368468

software Defined Network (SDN) represents a novel approach to network programming for the design, construction, and administration of computer networks. This approach entails the separation of the control plane from the data plane, with the objective of centralizing the network and consolidating all settings in the control plane. Network design frequently encounters challenges pertaining to network security and network attacks. SDN offers a number of advantages. One such advantage is that it allows the implementation of control functions at the controller level, thus positioning the controller as a key element of SDN. The centralized nature of SDN renders it susceptible to attacks, including Distributed Denial of Service (DDo $S$ ) attack. Consequently, a security system is required to address the issue of attacks directed towards the SDN controller. DDoS attack detection system is created using a machine learning algorithm, namely Random Forest, whose algorithm performance is optimized using Hyperparameter Tuning to achieve high accuracy in the detection process. The InSDN dataset, comprising a total of 56 classes, was employed in this research, and the SelectFromModel feature selection method was utilized to identify crucial features within the InSDN dataset. The method was found to be effective in detecting DDoS attacks, with an accuracy value of 99.99%. The results demonstrate that Hyperparameter Tuning Random Forest is an effective method for detecting DDoS attacks on SDN.

关键词： Machine learning algorithms Accuracy software algorithms Programming Network security Denial-of-service attack software defined networking Computer crime Tuning Random forests

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Profiling in the ASP codesign environment

Profiling in the ASP codesign environment

引用

International Symposium on System Synthesis

作者： M.F. Parkinson S. Parameswaran Department of Electrical and Computer Engineering University of Queensland Brisbane QLD Australia

Automation of the hardware/software codesign methodology brings with it the need to develop sophisticated high-level profiling tools. This paper presents a profiling tool which uses execution profiling on standard C code to obtain accurate and consistent times at the level of individual compound code sections. This tool is used in the ASP Hardware/software Codesign project. The results from this tool show that profiling must be performed on dedicated hardware which is as close as possible to the final implementation, as opposed to a workstation.

关键词： Application specific processors Hardware Partitioning algorithms software algorithms Algorithm design and analysis Costs Field programmable gate arrays Code standards Design methodology software performance

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Utilization of Deep Learning and Machine Learning algorithms in Detection, Segmentation, and Classification of Brain Metastasis: A Systematic Literature Review

Utilization of Deep Learning and Machine Learning Algorithms...

引用

IoT, Communication and Automation Technology (ICICAT), International Conference on

作者： Deepinder Kaur Jaspreet Singh Department of CSE Chandigarh University Mohali

ISBN: (数字)9798350368109

ISBN: (纸本)9798350368116

One-tenth to around a quarter of cancer patients lose their lives to Brain Metastasis (BM) globally. Accurate neuroimaging of BM is essential to encourage early detection, decide treatment options, and increase survival rates. This systematic literature review (SLR) examines the utilization of machine/deep learning algorithms and imaging modalities in the detection, segmentation, and classification of BM. The study adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement) and meticulously evaluates 32 relevant articles spanning from 2018 to 2023. The investigation explores scholarly databases including Google Scholar, SCOPUS, Web of Science, PubMed, SCISPACE, IEEE, Science Direct, Hindawi, and EBSCOhost to pull out relevant studies. The four aspects viz. employment of various imaging modalities, utilization of machine/deep learning algorithms, evaluation of performance metrics, and investigation of software tools for the identification of BM considered in this study. The review identifies Convolutional Neural Networks (CNN) as the most frequently utilized algorithm with the highest AUC-ROC (0.98) and demonstrates its efficacy for BM detection. Furthermore, out of 32, 15 articles highlight the significance of contrast-enhanced T1weighted images (T1CE/ T1c). This SLR unearths the transformative impact of machine/deep learning algorithms and emphasizes the importance of imaging modalities for enhancing the accuracy of diagnostics.

关键词： Deep learning Image segmentation Machine learning algorithms Accuracy software algorithms Imaging Metastasis Classification algorithms Convolutional neural networks Systematic literature review

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Comparative Study of Active Power Filters with Least Mean Square algorithm and conventional strategy in discrete-time domain

Comparative Study of Active Power Filters with Least Mean Sq...

引用

IEEE International Conference on Aerospace and Signals (INCAS)

作者： I. Delgado G.R.V Ponce Susan Machaca Ester Mendoza Eyner Calcina Professional School of Electronic Engineering National University of Altiplano Puno Perú

ISBN: (数字)9798331534233

ISBN: (纸本)9798331534240

This paper compares the performance of an active power filter implemented using the Least Mean Square (LMS) algorithm, with that of the traditional filter. An active power filter is designed to improve power quality in an electrical system. This entails reducing harmonics and reactive power, as well as eliminating unbalance. Since the LMS algorithm is among the fastest and simplest filters, which tends to make it easy to implement, the performance is evaluated using the Fast Fourier Transfer. Performance indicators for this application considered are harmonic removal and the stability period. The simulations are implemented in Matlab software, and the results allow a comparison of the LMS-based APF and reflect when the method is better and when it is necessary to have to stick to the traditional one. The LMS algorithm demonstrates results due to its ability to adapt to changes in real-time operation even under varying load operation frequency. This paper presents the mathematical model of two strategies of power compensation in continuous and discrete-time domain.

关键词： Reactive power Power filters software algorithms Power quality Signal processing algorithms Filtering algorithms Active filters Harmonic analysis Stability analysis Power harmonic filters

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Boundary-aided Extreme Value Detection based pre-processing algorithm for H.264/AVC fast intra mode prediction

Boundary-aided Extreme Value Detection based pre-processing ...

引用

IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)

作者： Chen-Hsien Miao Chih-Peng Fan Department of Electrical Engineering National Chung Hsing University Taichung Taiwan

The mode decision in the intra prediction of an H.264/AVC encoder requires complex computations and a significant amount of time to select the best mode that achieves the minimum rate-distortion (RD). The complex computations for the mode decision cause difficulty in real-time applications, especially for software-based H.264/AVC encoders. This study proposes an efficient fast algorithm called Boundary-aided Extreme Value Detection (BEVD) to predict the best direction mode, excluding the DC mode, for fast intra-mode decision. The BEVD-based edge detection can predict luma-4×4, luma-16×16, and chroma-8×8 modes effectively. The first step involves using the pre-processing mode selection algorithm to find the primary mode that can be selected for fast prediction. The second step requires applying the selected fewer high-potential candidate modes to calculate the RD cost for the mode decision. The encoding time is largely reduced, and similar video quality is also maintained. Simulation results show that the proposed BEVD method reduces encoding time by 63 %, and requires a bit-rate increase of approximately 1.7 %, and a decrease in peak signal-to-noise ratio (PSNR) by approximately 0.06 dB in QCIF and CIF sequences, compared with the H.264/AVC JM 14.2 software. The proposed method achieves less PSNR degradation and bit-rate increase compared to previous methods with more encoding time reduction.

关键词： Encoding Video coding PSNR Prediction algorithms software algorithms Cost function software

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