10th Symposium on Neural Network Applications in Electrical Engineering最新文献

Packet routing in wireless mesh networks 无线网状网络中的分组路由

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644081

N. Kojić, M. Zajeganovic-Ivancic, I. Reljin, B. Reljin

{"title":"Packet routing in wireless mesh networks","authors":"N. Kojić, M. Zajeganovic-Ivancic, I. Reljin, B. Reljin","doi":"10.1109/NEUREL.2010.5644081","DOIUrl":"https://doi.org/10.1109/NEUREL.2010.5644081","url":null,"abstract":"Wireless mesh networks (WMN) represent a type of mobile ad-hoc networks. These networks are very important in providing the Internet access to fixed and mobile terminal equipment. The main problem in WMNs (regarding to mesh routers and mesh clients) is a routing protocol, especially because it has to enable the access to network for both mesh and conventional clients. Access to Internet for wireless mesh networks is done via special mesh routers, the gateways. Several gateways may exist in a network. The main role of a routing protocol is to find way to establish connection between an end user and one of the gateways, as fast as possible, considering links status. This path should be optimized from the traffic distribution and path distance point. This paper presents one type of packet routing in wireless mesh networks based on Hopfield neural network. Artificial intelligence is used for path optimization. Distribution of local routing information and routing table updates is realized by mobile agents. In this way, network should have a simple way of routing information delivery and thus for effective user traffic support.","PeriodicalId":227890,"journal":{"name":"10th Symposium on Neural Network Applications in Electrical Engineering","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116417638","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

Artificial neural networks broken rotor bars induction motor fault detection 人工神经网络转子断条感应电动机故障检测

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644051

D. Matic, F. Kulić, V. Climente-Alarcon, R. Puche-Panadero

引用次数: 16

An EMG system for studying motor control strategies and fatigue 用于研究运动控制策略和疲劳的肌电图系统

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644044

M. Janković, D. Popović

{"title":"An EMG system for studying motor control strategies and fatigue","authors":"M. Janković, D. Popović","doi":"10.1109/NEUREL.2010.5644044","DOIUrl":"https://doi.org/10.1109/NEUREL.2010.5644044","url":null,"abstract":"We present a system for polymyographic analysis which addresses detection of muscle fatigue and strategies assumed by the central nervous system to deal with it. The system consists of EMG amplifiers, force transducers, A/D converter, portable computer and software running in the LabView environment that allows real-time and detailed offline processing of EMG signals in time and frequency domains. We demonstrate the features of the system by using the example of analyzing the strategy to generate 80% percent of the maximum force for prolonged period of time. Force sensor was used to detect muscle fatigue (fall of the force bellow the selected threshold), and EMG recordings were used for the analysis which of the quantitative measures of EMG is correlated with this. We tested the following four methods of EMG measures: 1) median frequency, 2) short-time mean frequency, 3) mean frequency of scalogram and 4) fractal dimension. We show that the system is capable of providing reproducible results and could be used for diagnostics and basic research in motor control. The analysis shows that the median frequency used often is not the best predictor of fatigues, and the measure needs to be selected based on the relative activity of the muscle compared to its maximal activity.","PeriodicalId":227890,"journal":{"name":"10th Symposium on Neural Network Applications in Electrical Engineering","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128643368","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: 11

Text line segmentation by adapted water flow algorithm 基于自适应水流算法的文本线分割

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644057

D. Brodic, Z. Milivojevic

引用次数: 6

Region-based phonocardiogram event segmentation in spectrogram image 基于区域的声谱图事件分割

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644108

A. Gavrovska, M. Paskas, D. Dujković, I. Reljin

引用次数: 4

High-speed implementation of Hamming neural network 汉明神经网络的高速实现

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644080

Vladimir B. Kovacevic, A. Gavrovska, M. Paskas

引用次数: 2

Singularly impulsive mathematical model of Delta — Notch signaling system Delta - Notch信号系统的奇异脉冲数学模型

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644100

N. Kablar

引用次数: 0

Microwave applicators modeling — Alternative approaches based on neural networks incorporating domain knowledge 微波应用器建模。基于结合领域知识的神经网络的替代方法

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644104

Z. Stanković, B. Milovanovic, N. Dončov, M. Milijić

引用次数: 1

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644099

N. Misic

{"title":"The self-similar numbers as a special case of cyclic numbers and their relation to the cyclic (genetic) codes","authors":"N. Misic","doi":"10.1109/NEUREL.2010.5644099","DOIUrl":"https://doi.org/10.1109/NEUREL.2010.5644099","url":null,"abstract":"The genetic code is analyzed as one of the major natural codes, which as such can reveal the deeper principles of optimal coding. The analysis is based on a discovery that the symmetrical architecture of genetic code and the nucleon number of its constituents — the free canonical amino acids and bases, are strictly determined by the prime number with a cycling digit property −037. A detailed derivation for all types of analogues of 037 is given and shown that they represent a special case of cyclic numbers whose digits and multipliers are equidistant. The derived generic formula for analogues of 037 is correlated with cyclotomic and generalized Golden Mean polynomials, by which is shown their relation with discrete self-similarity, why author named them the Self-similar Numbers. Also it is given their relationship with the cyclic codes, which is with fact that the genetic code is arranged in multiple ways at different levels as a cyclic code, generally indicate that the hierarchically nested cyclicality is one of the principles of fractal organization of the genetic code, as well as the other organic codes in the living organisms.","PeriodicalId":227890,"journal":{"name":"10th Symposium on Neural Network Applications in Electrical Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114436174","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: 3

Action representation for Wii bowling: Classification Wii保龄球的动作表示:分类

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644043

M. Kostic, D. Popović

引用次数: 3