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检索条件"主题词=Filtering algorithms"

共 10349 条记录，以下是761-770 订阅

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Synthesis of a Two-Stage Algorithm for Estimating Antenna Array Orientation Angles from GNSS Signals

Synthesis of a Two-Stage Algorithm for Estimating Antenna Ar...

引用

International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Artyom D. Evseev Stepan V. Orobchenko Kirill V. Kochka Alexander A. Chugunov Nikita I. Petukhov Alice O. Kozhevnikova Radio Systems Department National Research University “MPEI” Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Global Navigation Satellite Systems (GNSS) have become part of everyday human life. It is impossible to imagine transportation, unmanned aerial vehicles, as well as land surveying and geodesy without GNSS. In addition to determining the exact location of objects, GNSS receiver is used to solve the problem of determining the user's orientation angles from signals. The mode of determining the spatial orientation of mobile objects based on the results of measuring the parameters of navigation satellite (NS) received by spatially separated antennas is one of the most promising directions for expanding the functionality of GNSS. Both one-step and filtering algorithms for estimating consumer spatial orientation are common today. Thus, the purpose of this paper is to carry out the synthesis of a two-step algorithm for estimating antenna array orientation angles from GNSS signals, and to carry out simulation modeling of the synthesized algorithm. The object of the study is a two-step algorithm for estimating the orientation angles of an antenna array. As a result of the study, a two-stage algorithm for antenna array orientation angle estimation was developed and simulation modeling was performed. The root-mean square deviation of the course angle estimates was 0.01 degrees.

关键词： Antenna measurements Global navigation satellite system Satellite antennas Satellites Simulation Transportation Receiving antennas filtering algorithms Antenna arrays Signal to noise ratio

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An optimized Clisteer Long-Range Kookaburra Attention Module Steerable Convolutional Neural Networks for Crime Predictions in Smart Cities

An optimized Clisteer Long-Range Kookaburra Attention Module...

引用

Data Science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： R.Ramji S Devi Department of Electronics and Communication Engineering PRIST Deemed to be University Thanjavur Tamil Nadu India Department of Electronics and Communication Engineering Sree Venkateswara College of Engineering Nellore Andhra Pradesh India

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

Crime prediction in smart cities is a complex yet promising field that leverages data and technology to enhance public safety. In the previous papers several deep learning algorithms are used to predict the crimes in smart cities but does not provide sufficient results that is accuracy is decreased, error rate, computational time, cost is increased. To overcome these limitations this work is proposed. In this manuscript, an optimized Clisteer Long-Range Kookaburra Attention Module Steerable Convolutional Neural Networks (2CLR-KoobAtMSNet) for Crime Predictions in Smart Cities is proposed to predict the crimes in smart cities. In this, to predict the crimes the input dataset is taken from crime data for city of Chicago city. Then these data are cleaned using the Adaptive Guided Side Window Box Filter with Multiple Layers (AGS-WBF-ML). Then the features are extracted using the Attention based Swin Transformer (AST). After that, the features are selected using the Dung Beetle Optimization Algorithm (DBOA) for crime prediction. Finally, the crimes are predicted using the 2CLR-KoobAtMSNet. The 2CLR-KoobAtMSNet model was implemented on the Python platform and evaluated using four datasets, achieving remarkable results with 99.9% accuracy and 99.8% recall, outperforming existing methods. These results demonstrate the model’s exceptional effectiveness and opportunities for advancement in customized stress-reduction strategies.

关键词： Adaptation models Accuracy Smart cities filtering algorithms Prediction algorithms Feature extraction Transformers Convolutional neural networks Optimization Stress

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Better Exploiting Spatial Separability in Multichannel Speech Enhancement with an Align-and-Filter Network

Better Exploiting Spatial Separability in Multichannel Speec...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ching-Hua Lee Chouchang Yang Yashas Malur Saidutta Rakshith Sharma Srinivasa Yilin Shen Hongxia Jin AI Center-Mountain View Samsung Electronics

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Multichannel speech enhancement (SE) techniques combine multiple microphone signals to extract clean speech from noisy mixtures based on spatial filtering. As the target speech may come from arbitrary, unknown directions, current deep learning-based SE systems could suffer from performance bottleneck in denoising speech within one stage. In contrast, conventional signal processing algorithms often feature a two-stage design, where the first stage focuses on spatially aligning the received signals with respect to the speech source, followed by the second stage to filter out noise. In this paper, we introduce Align-and-Filter network (AFnet) for deep learning-based SE that decouples the primal denoising problem into two sub-problems, which imitates the alignment-followed-by-filtering wisdom from signal processing. The key is to leverage the relative transfer functions (RTFs) that encode meaningful spatial information via a tactically designed alignment strategy. Experimental results show that by leveraging the proposed RTF-based spatial alignment supervision, AFnet learns interpretable directional features to better exploit spatial separability of sound sources for improved SE performance.

关键词： Uncertainty Noise reduction Noise Transfer functions Signal processing algorithms Speech enhancement filtering algorithms Information filters Noise measurement Microphones

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An Efficient Designated Dating Matching Scheme for Online Social Network

An Efficient Designated Dating Matching Scheme for Online So...

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IEEE International Conference on Big Data Security on Cloud (BigDataSecurity), High Performance and Smart Computing (HPSC) and Intelligent Data and Security (IDS)

作者： ChaoLiang Li Qiang Dou XuWei Zhu JiYan Liu Hua Huang School of Computer Science Hunan University of Technology and Business Changsha China School of Intelligent Engineering and Intelligent Manufacturing Hunan University of Technology and Business Changsha China

ISBN: (数字)9798331595104

ISBN: (纸本)9798331595111

The significance of privacy and security in online social networks is to protect sensitive information, prevent unauthorized access, and build trust among users while ensuring a secure online environment. This paper proposes a friendship matching system based on the Parlier encryption algorithm, aiming at addressing existing privacy breaches and data misuse issues on current friendship platforms, significantly improving matching accuracy. First, filter the data items that users care about more in the database so as to make the appropriate friends. Then, according to the homomorphic encryption of paillier algorithm, in the case of ciphertext, the weight of each data item is calculated to the selected users. Finally, the Euclidean distance is used to calculate the similarity between users and select the appropriate dating users. Experimental results demonstrate that the proposed system exhibits strong performance and feasibility in preserving user privacy and data security.

关键词： Data privacy Matched filters Social networking (online) Databases Euclidean distance filtering algorithms Privacy breach Information filters Protection Homomorphic encryption

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A Modified Gain Normalized Step Size Adaptive Algorithm for Improved Online Secondary Path Modelling in Active Noise Control

A Modified Gain Normalized Step Size Adaptive Algorithm for ...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Asutosh Kar Gagandeep Singh Pradeep K. Shill Somanath Pradhan Vasundhara M. G. Christensen Department of Electronics and Communication Engineering Dr. B. R. Ambedkar National Institute of Technology Jalandhar Punjab India Department of Electrical Engineering Indian Institute of Technology Patna Bihar India Department of Electronics and Communication Engineering National Institute of Technology Warangal Telangana India Department of Electronic Systems Aalborg University Aalborg Denmark

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The noise cancellation performance of an active control system decreases when there are temporal variations in the primary and secondary paths. An active noise control (ANC) framework has been introduced in this work, which incorporates four adaptive filters and two decorrelation filters for online secondary path modelling. A novel adaptive algorithm for an active noise control filter has been developed with the combination of modified gain filtered-x recursive least square and normalised step size filtered-x least mean square. The aim is to improve the reduction of mean noise and decrease residual noise while maintaining consistent convergence rate. To update the decorrelation filters in the framework, an adaptive variable step size modified decorrelation normalised least mean square algorithm has been used. These filters are designed to maximize the efficiency of secondary path modelling. Compared to its counterparts, the simulation results illustrate the enhancements of the proposed framework without a substantial increase in overall computational complexity.

关键词： Adaptation models Filters Computational modeling Noise Signal processing algorithms Adaptive filters filtering algorithms Decorrelation Computational complexity Convergence

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kXpert Profiling System using Unsupervised Keyword Extraction

kXpert Profiling System using Unsupervised Keyword Extractio...

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International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Nur Atiqa Basaruddin Bazilah A. Talip Shahrinaz Ismail Centre for Women Advancement & Leadership (CWAL) Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia Knowledge Artificial Intelligence Learning & Automation (KAiLA) Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia School of Technology Asia Pacific Asia Pacific University of Technology and Innovation (APU) Kuala Lumpur Malaysia

ISBN: (数字)9798331507817

ISBN: (纸本)9798331507824

Developing an expert system for identifying experts is crucial for organisation especially higher institution. Finding an expert is challenging because some of the researchers are not frequently update their profile, which significantly influenced on potential research collaboration and student intake in post-graduate studies. This impact has indirectly shown the importance of implementing new method in search for experts, with expertise verified by trusted information resources. The kXpert profiling framework is proposed as a design of a new expert finding system using unsupervised keyword extraction algorithm and data filtering. The algorithms used in this system were RAKE, YAKE and Key-BERT, in which KeyBERT is found to be the most accurate among the three algorithms. The system is expected to reduce the time and effort required to engage in discussion with an individual to determine whether he or she is the correct expert in need

关键词： Accuracy Information resources Tagging filtering algorithms Information filters Classification algorithms Information management Data mining Object recognition Expert systems

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Estimated Load Feedforward instead of Voltage Integrator for Phase-Shifted Full Bridge Converter to Enhance Transient Response

Estimated Load Feedforward instead of Voltage Integrator for...

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International Conference on Power Electronics and Motion Control (IPEMC)

作者： Mingyu Xue Bin Cao Kaiwei Cao Haicong Zhang Jifeng Chen Xu Chu Xiaohua Jiang Department of Medical Power Solutions United-Imaging Healthcare Co. Shanghai China Department of Electrical Engineering Tsinghua University Beijing China

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

A novel control algorithm for the phase-shifted full bridge converter is proposed that employes proportional controller for the voltage loop and proportional-integral controller for the current loop. Besides, estimated load feedforward is adopted using the filtered primary current. Moreover, the voltage integrator is removed to avoid its deterioration to transient response. In such a way, both infinity open-loop dc gain and attenuated output impedance are achieved, leading to precise regulation and fast response. Only output voltage and primary current are sensed, whose sampling-gain drifts are tolerable. Simulation and experiment results verify the methodology.

关键词： Transient response PI control Asia Bridge circuits filtering algorithms Regulation Power electronics

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Harnessing Text Analysis for Automated Document Understanding

Harnessing Text Analysis for Automated Document Understandin...

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International Conference on Advances in Information Technology (ICAIT)

作者： Tushar Bharadwaj Swarit Ajay Sartaj Ahmad KIET Group of Institutions Delhi-NCR Ghaziabad Uttar Pradesh India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

This paper is about Text Summarization based on NLP. We are using Python programming language to build that paper. Project works well on both small as well as large datasets. To construct the paper, we used a thorough approach. To begin, the text was tokenized to divide it into smaller components. Following that, the data was preprocessed to ensure that it was clean and ready for future investigation. A histogram table was then generated to demonstrate the frequency distribution of words or phrases within the text. To enhance this representation, we created a weighted histogram table, which most likely includes attributes such as word importance or relevance. Then, for each phrase, a score was assigned depending on certain criteria, maybe connected to its importance or relevance to the total text. Following that, the scores were arranged in descending order to highlight the most important lines. Finally, the final overview of the project was prepared utilizing. The final summary is provided on the concept of the sentence which has the highest sentence score based on that we filter it. The primary goal is to use well methodologies and algorithms that equip machines with the capability to understand, interpret and extract information from a wide range of textual materials. In real-life it helps the people to save their lots of time and efforts sothat they can easily read and understand the whole article meaning in lesser time.

关键词： Histograms Text summarization filtering algorithms Information filters Information technology Python

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引用

International Conference on Data Engineering

作者： Hanchen Wang Jianke Yu Xiaoyang Wang Chen Chen Wenjie Zhang Xuemin Lin Zhejiang Gongshang University China University of Technology Sydney Australia University of New South Wales Australia University of Wollongong Australia Shanghai Jiao Tong University China

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Supergraph search is a fundamental graph query processing problem. Supergraph search aims to find all data graphs contained in a given query graph based on the subgraph isomorphism. In other words, the goal is to determine if part of the query graph is the same as a smaller data graph. Existing algorithms construct the indices and adopt the filtering-and-verification framework, which is usually computationally expensive and can cause redundant computations. Recently, various learning-based methods have been proposed for a good trade-off between accuracy and efficiency for query processing tasks. However, to our knowledge, no learning-based method is proposed for the supergraph search task. In this paper, we propose the first learning-based method for similarity search on supergraph containment, named Neural Supergraph similarity Search (NSS). NSS first learns the representations for query and data graphs and then efficiently conducts the supergraph search on the representation space, the complexity of which is linear to the number of data graphs. The carefully designed Wasserstein discriminator and reconstruction network enable NSS to capture better the interrelation, structural and label information between and within the query and data graphs. Experiments demonstrate that the NSS is up to 6 orders of magnitude faster than the state-of-the-art exact supergraph search algorithm in query processing and is more accurate than the other learning-based solutions.

关键词： Learning systems Accuracy Query processing filtering algorithms Search problems Data engineering Complexity theory

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Conditions of Informational Signal Receiving by Land Based Adaptive Antenna Arrays of Global Navigation Satellite Systems

Conditions of Informational Signal Receiving by Land Based A...

引用

Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Victor I. Djigan Institute of Microdevices and Control Systems National Research University of Electronic Technology Moscow Russia

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

This paper presents a methodology for assessing the possibility to receive the signals from the Global Navigation Satellite Systems (GNSS) by the receivers with the Adaptive Antenna Arrays (AAA). The methodology is based on the estimation of the steady-state Signal-to-Noise Ratio (SNR) at the AAA output. The SNR is estimated over all the possible directions of the signal source angular locations. This methodology is demonstrated by using the examples of the steady-state behavior of the widely used Side Lobe Canceller (SLC) AAA and the Linearly Constrained (LC) AAA with the beam constraint. The simulation demonstrates that the satellite signals can be received from about 30% directions of the spherical angular space in the case of a rectangular AAA with $2 \times {4}$ antennas after the suppressing of 7 interfering signals. It is about a 10% bigger value comparing to that of the AAA in the initial nonadaptive stage. If to consider the upper hemisphere of space only, then this value is doubled. In this experiment, both of the considered AAA demonstrate about the same performance from the interference suppression and informational signals receiving points of view. This efficiency might be different in another scenario. The generic architecture and computational procedures of the AAA used in the considered simulations and computations are also presented. The procedures are based on the usage of the Recursive Least Squares adaptive filtering algorithm.

关键词： Interference suppression Global navigation satellite system Satellite antennas Adaptive systems Satellites Adaptive arrays Receiving antennas filtering algorithms Steady-state Signal to noise ratio

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