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12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)最新文献

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Battery operated smart device for human movement measurement based on android OS platform and bluetooth technology 基于android操作系统平台和蓝牙技术的电池供电人体运动测量智能设备
12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) Pub Date : 2014-11-01 DOI: 10.1109/NEUREL.2014.7011497
Nikola S. Cakic, M. Popovic
{"title":"Battery operated smart device for human movement measurement based on android OS platform and bluetooth technology","authors":"Nikola S. Cakic, M. Popovic","doi":"10.1109/NEUREL.2014.7011497","DOIUrl":"https://doi.org/10.1109/NEUREL.2014.7011497","url":null,"abstract":"Battery operated small, portable and mobile device based on micro-electro-mechanical sensor (MEMS) integrating tri-axis gyroscope, tri-axis accelerometer and Digital Motion Processor™ (DMP) was developed. Device implements Bluetooth module for communication with Android gadget where data acquisition is performed in developed Android application. Implemented components provide wireless battery operated smart mobile device suitable for human movement assessment. This device may be used for data acquisition during motion to estimate kinematics in humans with motor disability.","PeriodicalId":402208,"journal":{"name":"12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130570989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Behavioral modeling by Volterra series and time-delay neural network approach 基于Volterra级数和时滞神经网络方法的行为建模
12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) Pub Date : 2014-11-01 DOI: 10.1109/NEUREL.2014.7011456
Jelena Misic, V. Markovic, Z. Marinković
{"title":"Behavioral modeling by Volterra series and time-delay neural network approach","authors":"Jelena Misic, V. Markovic, Z. Marinković","doi":"10.1109/NEUREL.2014.7011456","DOIUrl":"https://doi.org/10.1109/NEUREL.2014.7011456","url":null,"abstract":"Solving the non-linear distortion problems in wireless communications is often based on developing the behavioral models of non-linear components. In this paper, a non-linear Volterra model up to third order is developed by using an artificial neural network (ANN) approach. The Volterra kernels are derived from the parameters of a feed-forward time delay neural network with a suitable activation function. The Volterra model is implemented to represent the behavior of a low noise amplifier for LTE receiver.","PeriodicalId":402208,"journal":{"name":"12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)","volume":"39 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123673584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Pulse rate assessment: Eulerian Video Magnification vs. electrocardiography recordings 脉搏率评估:欧拉视频放大vs.心电图记录
12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) Pub Date : 2014-11-01 DOI: 10.1109/NEUREL.2014.7011447
N. Miljković, D. Trifunović
{"title":"Pulse rate assessment: Eulerian Video Magnification vs. electrocardiography recordings","authors":"N. Miljković, D. Trifunović","doi":"10.1109/NEUREL.2014.7011447","DOIUrl":"https://doi.org/10.1109/NEUREL.2014.7011447","url":null,"abstract":"Non contact pulse rate assessment is of interest for patients with cardio-vascular diseases. We tested the feasibility of the use of regular web camera for pulse rate assessment. The Eulerian Video Magnification was used for processing of acquired video sequences. The results were compared with the pulse rate determined from the electrocardiography signals, recorded from the two electrodes positioned at left side of the chest. We present pulse rate results obtained from both methods recorded from two healthy volunteers. The comparison shows that the Eulerian Video Magnification differs from the electrocardiography for less than 5% at normal pulse rate. The results show that for heart rates that correspond to cardio-vascular diseases (e.g. tachicardia, bradicardia), the algorithm needs further modifications (higher quality camera is needed).","PeriodicalId":402208,"journal":{"name":"12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128647126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Platform for integration of internet games for the training of upper extremities after stroke 脑卒中后上肢训练网络游戏整合平台
12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) Pub Date : 2014-11-01 DOI: 10.1109/NEUREL.2014.7011495
Milena T. Okosanovic, J. Kljajic, M. Kostic
{"title":"Platform for integration of internet games for the training of upper extremities after stroke","authors":"Milena T. Okosanovic, J. Kljajic, M. Kostic","doi":"10.1109/NEUREL.2014.7011495","DOIUrl":"https://doi.org/10.1109/NEUREL.2014.7011495","url":null,"abstract":"The gaming system used during the process of neurorehabilitation is developed. It is composed of: acquisition component - Wacom Intuos4 XL tablet, and a computer which processes data and uses them as control signals in Internet game. Monitoring of either personal progress or success of other users using the presented platform is enabled by special evaluation system which provides comparison of the results. Quality of movement is assessed by the method which employs method of “Probability Tubes”. The result of this assessment is reflected in the form of a control signal adapted to playing online games Darts. The system supports point to point movements in horizontal plane.","PeriodicalId":402208,"journal":{"name":"12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117222701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Classifications of motor imagery tasks using k-nearest neighbors 基于k近邻的运动意象任务分类
12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) Pub Date : 2014-11-01 DOI: 10.1109/NEUREL.2014.7011475
Roxana Aldea, M. Fira, A. Lazar
{"title":"Classifications of motor imagery tasks using k-nearest neighbors","authors":"Roxana Aldea, M. Fira, A. Lazar","doi":"10.1109/NEUREL.2014.7011475","DOIUrl":"https://doi.org/10.1109/NEUREL.2014.7011475","url":null,"abstract":"We address a classification method for motor imagery tasks-based brain computer interface (BCI). The wavelet coefficients are used to extract the features from the motor imagery electroencephalographic (EEG) signals and the k-nearest neighbor classifier is applied to classify the pattern of left or right hand imagery movement and rest. The performance of the proposed method is evaluated using EEG data recorded with 8 g.tec active electrodes by means of g.MOBIlab+ module. The maximum classification accuracy is 91%.","PeriodicalId":402208,"journal":{"name":"12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114333488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Stock market trend prediction using a sparse Bayesian framework 基于稀疏贝叶斯框架的股票市场趋势预测
12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) Pub Date : 2014-11-01 DOI: 10.1109/NEUREL.2014.7011508
Ivana P. Markovic, Milos B. Stojanovic, M. Bozic
{"title":"Stock market trend prediction using a sparse Bayesian framework","authors":"Ivana P. Markovic, Milos B. Stojanovic, M. Bozic","doi":"10.1109/NEUREL.2014.7011508","DOIUrl":"https://doi.org/10.1109/NEUREL.2014.7011508","url":null,"abstract":"The aim of this study is to develop a relevance vector machine-a RVM classifier for trend prediction of the BELEX15 index of the Belgrade Stock Exchange. In addition, the RVM model is compared to two `similar' methods: support vector machines - SVMs and least squares support vector machines - LS-SVMs to analyze their classification precisions and complexity. The test results indicate tha tRVMs outperform benchmarking models and are suitable for short-term stock market trend predictions.","PeriodicalId":402208,"journal":{"name":"12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133303529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Fuzzy approach for evaluating risk of service interruption used as criteria in electricity distribution network planning 配电网中断风险评价的模糊评判方法
12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) Pub Date : 2014-11-01 DOI: 10.1109/NEUREL.2014.7011466
M. Saric
{"title":"Fuzzy approach for evaluating risk of service interruption used as criteria in electricity distribution network planning","authors":"M. Saric","doi":"10.1109/NEUREL.2014.7011466","DOIUrl":"https://doi.org/10.1109/NEUREL.2014.7011466","url":null,"abstract":"Electricity distribution network planning is a complex optimization process which requires assessment of various planning criteria. Planning is performed under conditions of system constraints, extreme uncertainty and information imperfection. It is possible, however, to obtain precise output value from imprecise input variables, in a process of fuzzy control. This paper proposes the application of Mamdani type fuzzy inference in modelling the risk of service interruption as one of the criteria used in distribution network planning.","PeriodicalId":402208,"journal":{"name":"12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)","volume":"4276 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126662299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Customer classification and load profiling using data from Smart Meters 使用来自智能电表的数据进行客户分类和负载分析
12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) Pub Date : 2014-11-01 DOI: 10.1109/NEUREL.2014.7011464
G. Grigoraș, O. Ivanov, M. Gavrilas
{"title":"Customer classification and load profiling using data from Smart Meters","authors":"G. Grigoraș, O. Ivanov, M. Gavrilas","doi":"10.1109/NEUREL.2014.7011464","DOIUrl":"https://doi.org/10.1109/NEUREL.2014.7011464","url":null,"abstract":"The paper presents a self-organization based integrated model for customer classification and load profiling in distribution systems. The consumer classification in consumption classes characterized by typical load profiles is made using information provided by Smart Meters. For determination of the consumption classes, every customer is characterized by the following primary information: daily (monthly) energy consumption, minimum and maximum loads. The proposed model was tested using household consumers from a rural area. The results demonstrate the ability of the methodology to efficiently used in distribution systems when information about the supplied customers is very poor (based only the data provided by classic meters).","PeriodicalId":402208,"journal":{"name":"12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129432747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 13
Applications of probabilistic model based on main quantum mechanics concepts 基于主要量子力学概念的概率模型的应用
12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) Pub Date : 2014-11-01 DOI: 10.1109/NEUREL.2014.7011453
M. Jankovic, Tomislav Gajić, B. Reljin
{"title":"Applications of probabilistic model based on main quantum mechanics concepts","authors":"M. Jankovic, Tomislav Gajić, B. Reljin","doi":"10.1109/NEUREL.2014.7011453","DOIUrl":"https://doi.org/10.1109/NEUREL.2014.7011453","url":null,"abstract":"Recently, the several applications of the probabilistic model based on two of the main concepts in quantum physics - a density matrix and the Born rule, have been introduced. It was shown that the model can be suitable for the modeling of learning algorithms in biologically plausible artificial neural networks framework, like it is the case of on-line learning algorithms for Independent /Principal/Minor Component Analysis, which could be realized on parallel hardware based on very simple computational units. Also, it has been shown that the quantum entropy of the system, related to that model, can be successfully used in the problems like change point detection, with some examples of applications in the area of power electronics and general classification problems. Here, we present a robust on-line Principal Component Algorithm based on the proposed model, which extracts several principal components simultaneously. Also, we will show usefulness of the proposed method in a simple example of image segmentation.","PeriodicalId":402208,"journal":{"name":"12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122895833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Simple fuzzy solution for quadrotor attitude control 四旋翼飞行器姿态控制的简单模糊解
12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL) Pub Date : 2014-11-01 DOI: 10.1109/NEUREL.2014.7011469
I. Petruševski, A. Rakic
{"title":"Simple fuzzy solution for quadrotor attitude control","authors":"I. Petruševski, A. Rakic","doi":"10.1109/NEUREL.2014.7011469","DOIUrl":"https://doi.org/10.1109/NEUREL.2014.7011469","url":null,"abstract":"This paper presents new computationally efficient and easy to tune attitude control of a four rotor helicopter called quadrotor. Short description of quadrotor concept and control framework is given and the segment of inner attitude control of the aircraft is addressed. Proposed fuzzy proportional - differential (PD) control structure utilizes Sugeno fuzzy engine, with simple intuitive set of rules and set of physically meaningful parameters. The verification of proposed solution was done via simulation and comparison with existing backstepping based attitude control system.","PeriodicalId":402208,"journal":{"name":"12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131752962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
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