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检索条件"任意字段=2nd International Conference on Signal and Data Processing, ICSDP 2022"

共 3153 条记录，以下是71-80 订阅

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data Mining Technology and Its Application in Multi-sensor data processing 2

Data Mining Technology and Its Application in Multi-sensor D...

引用

2nd IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2022

作者： Xu, Junjun Guo, Yunhui Wang, Jiang York University Liberal Arts and Professional Study Toronto Canada National University of Defense Technology Department of Communication Hefei China

ISBN: (纸本)9781665442763

Big data contains huge data value, can effectively promote the development of university information;However, there are many difficulties in the application of big data in multi-sensor data processing. In view of the practical problems faced by the current multi-sensor data processing and big data applications, the overall architecture design and the construction of core modules of multi-sensor data processing are carried out, including data acquisition, data governance, data storage, real-time computing and big data algorithm, data management, application service center and data security center. The application of multi-sensor data processing in data mining shows that it can meet the requirements of multi-sensor data processing and provide useful reference for multi-sensor data processing. © 2022 IEEE.

关键词： data mining

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Smart grid big data processing technology and cloud computing application status quo and challenges 2

Smart grid big data processing technology and cloud computin...

引用

2nd IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2022

作者： Yuanyuan, Ji Tianjin University of Technology Tianjin China

ISBN: (纸本)9781665442763

With the rapid development of China's economy, people's demand for electricity is increasing, so that the power grid will generate a large amount of data information in the actual operation, and the smart grid big data processing technology is to store and use the data information generated by the operation of the power *** ultimate purpose of applying big data processing technology is to make efficient use of the data information generated by the power grid, improve the rate of data access and processing, so as to provide necessary support and help for the normal operation of the power grid, and ensure that the national power grid can provide more stable power for people and *** paper focuses on the smart grid big data processing technology and opportunities and challenges. © 2022 IEEE.

关键词： Smart power grids

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Power Quality Assessment in a Microgrid System using signal Decomposition Techniques 2

Power Quality Assessment in a Microgrid System using Signal ...

引用

2nd international conference on Artificial Intelligence and signal processing, AISP 2022

作者： Panigrahi, Rasmi Ranjan Biswal, Monalisa Mishra, Manohar EE Department SOA University ITER Odisha Bhubaneswar India EE Department NIT Chhattisgarh Raipur India EEE Department SOA University ITER Odisha Bhubaneswar India

ISBN: (纸本)9781665442909

In this work, a report on different signal decomposition techniques (time-frequency TF) applied to power quality (PQ) events are provided. In a system with hybrid renewable sources, nonlinear load points and capacitor bank, the operation of individual units can affect the quality of the signals while switching from one state to another or during varying operating modes. In this context, the grid operating state is another concern which cannot be neglected. Considering the different possible operating states and operating conditions of system and individual equipment, different signal decomposition techniques are selected and the responses for individual events are analyzed. The Empirical Mode Decomposition (EMD), Ensembled Empirical Mode Decomposition (EEMD) and Intrinsic Time Decomposition (ITD) techniques are selected for signal analysis. Cases such as noise, harmonics, voltage sag, and nonlinear load switching events are simulated and presented in the work. © 2022 IEEE.

关键词： Empirical mode decomposition

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Eye-2-I: Eye-Tracking for Just-in-Time Implicit User Profiling 2

Eye-2-I: Eye-Tracking for Just-in-Time Implicit User Profili...

引用

2nd IEEE international conference on signal and Image processing (ICSIP)

作者： Ma, Keng-Teck Xu, Qianli Lim, Rosary Li, Liyuan Sim, Terence Kankanhalli, Mohan ASTAR Inst Infocomm Res 1 Fusionopolis Way Singapore 138632 Singapore Natl Univ Singapore 13 Comp Dr Singapore 117417 Singapore

ISBN: (纸本)9781538609699

For many applications, such as targeted advertising and content recommendation, knowing users' traits and interests is a prerequisite. User profiling is a helpful approach for this purpose. However, current methods, i.e. self-reporting, web-activity monitoring and social media mining are either intrusive or require data over long periods of time. Recently, there is growing evidence in cognitive science that a variety of users' profile is significantly correlated with eye-tracking data. A novel just-in-time implicit profiling method, Eye-2-I, which learns the user's demographic and personality traits from the eye-tracking data while the user is watching videos is proposed. Although seemingly conspicuous by closely monitoring the user's eye behaviors, the proposed method is unobtrusive and privacy-preserving owing to its unique combination of speed and implicitness. As a proof-of-concept, the proposed method is evaluated in a user study with 51 subjects.

关键词： eye-gaze user profiling classification machine learning

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A Fuzzy-GRNN Classifier for Pattern Recognition 2

A Fuzzy-GRNN Classifier for Pattern Recognition

引用

2nd international conference on signal processing and Integrated Networks (SPIN)

作者： Verma, Prabha Singh, Prashant Yadava, R. D. S. Banaras Hindu Univ Sensors & Signal Proc Lab Dept Phys Varanasi 221005 Uttar Pradesh India

ISBN: (纸本)9781479959914

We present a scheme for combining fuzzy c-means clustering with generalized regression neural network for improving its pattern classification efficiency. The membership grades of data points produced by fuzzy c-means clustering have been used to define weights for data points in the feature space according a logarithmic measure of uncertainty similar to the Shannon's entropy. The method improves classification results from 1% to 17% for 9 data sets analyzed here.

关键词： Fuzzy uncertainty Ferature vector weighting Generalized regression neural network calssifier

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Recursive Matrix Pencil Method 2

Recursive Matrix Pencil Method

引用

2nd international Ural conference on Measurements (UralCon)

作者： Ibryaeva, O. South Ural State Univ Chelyabinsk Russia

ISBN: (纸本)9781538605219

The main concern for many applications (for example, for Coriolis Mass Flow Meter signal processing in two-phase flow conditions) is to track several domain poles of signals with minimum delay. The Matrix Pencil method (MPM) estimates the signal as a sum of complex exponentials. Creating a computationally efficient moving MPM implementation is of a high interest. The most computationally expensive step of the classical MPM is to calculate the singular value decomposition (SVD) of a matrix composed from the signal samples. When a new data point enters the data window, this matrix changes only slightly, and it is reasonable to find its SVD not directly but using the SVD of the old matrix and a low-rank SVD modification procedure. In this paper a well-known SVD modification procedure is adapted for MPM and a recursive version of MPM is proposed. The amended method is validated by numerical examples and is faster than the original suggesting it may be feasible to track signal parameters on-line. The errors accumulating over time due to the recursive calculation require the recursive MPM to be restarted periodically.

关键词： matrix pencil method prony-like methods recursive estimation singular value decomposition (SVD) updating and downdating SVD coriolis mass flow meter signal processing

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CNN based Static Hand Gesture Recognition using RGB-D data 2

CNN based Static Hand Gesture Recognition using RGB-D Data

引用

2nd international conference on Artificial Intelligence and signal processing, AISP 2022

作者： Kumar, Dayananda N.C. Suresh, K.V. Dinesh, R. Dept. of Electronics and Communication Siddaganga Institute of Technology Tumkur India Dept. of Information Science and Engineering Jain University Bangalore India

ISBN: (纸本)9781665442909

Hand gesture recognition refers to identification of various hand postures which interprets the signs of non verbal communication. It finds various applications like Sign Language Recognition (SLR), Human Computer Interaction (HCI) for robotics control, 3D modeling etc., Efficiently recognizing the hand gestures in various complex background scenarios is still a challenging problem. This issue can be effectively addressed by using depth data as a additional cue along with RGB image. Depth refers to the distance between camera sensor and image scene, hence depth cues can be used in suppressing the complex backgrounds which are far away from the hand region. Depth can also be effectively used to handle the illumination issues. In this paper, we propose a two stage approach where first stage involves k-means algorithm based depth clustering and removal of the background region. In the later stage, the foreground filtered depth map is fused with RGB and the resultant RGB-D data is used for gesture recognition using Convolutional Neural Network (CNN) classification model. Experiments are conducted on OUHAndS datasets and the results are compared with well known existing methods. Experimental result shows that accuracy of 87.57% can be achieved on OUHAndS test dataset using the proposed method. © 2022 IEEE.

关键词： 3D modeling

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Study on data Clustering and Intelligent Decision Algorithm of Indoor Localization 2

Study on Data Clustering and Intelligent Decision Algorithm ...

引用

2nd international conference on Communication, Image and signal processing (CCISP)

作者： Liu, Zexi Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

关键词： Redundancy

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Analysis of vibration signal processing

Analysis of vibration signal processing

引用

2nd international Symposium on Test and Measurement (ISTM/97)

作者： Yang, JJ Guo, NL Han, XM Air Force Missile Inst Shaanxi China

ISBN: (纸本)7800033910

For the purpose of fault diagnosis, a synthesis signal processing method was employed In certain mechanical fault diagnosis system. Several useful technologies were adopted in the system, such as fuzzy theory correlation analysis, data base and parameter identification technology The computer program was built based on these technologies The principle and the steps used In this system can be used in other similar fault diagnosis system as well.

关键词： Vibrations (mechanical)

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Big data Analysis of Intelligent Emotion Recognition Based on ECG signal processing Technology 2

Big Data Analysis of Intelligent Emotion Recognition Based o...

引用

2nd IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2022

作者： Gong, Zekai Li, Xiaoyu Zhang, Xinyu Bell Honor School Nanjing University of Posts and Telecommunications Jiangsu Nanjing210023 China Department of Electrical and Electronic Engineering Xi'An Jiaotong-Liverpool University Jiangsu Suzhou215123 China Department of Electronics and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9781665442763

ECG signals appear more and more frequently in people's lives. Through ECG signals, we can learn some of the most basic physiological information of the human body. Through the physiological information, we can analyze and diagnose the physiological condition of the patient. In addition, the portability of ECG measurement equipment also provides researchers with more possibilities. This article discusses the design scheme of ECG front-end analog circuits, combines the obtained results with the cutting-edge theory of emotion recognition, and proposes the advantages and disadvantages of different circuit design schemes and algorithms. This article also analyzes the specific parameters of circuit design and the comparison of data processing algorithms, aiming to explore more applications of ECG signals in the field of emotion recognition. © 2022 IEEE.

关键词： Emotion Recognition

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