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2006 8th Seminar on Neural Network Applications in Electrical Engineering最新文献

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Regional Models for Biological Processes Based on Linear Regression and Neural Networks 基于线性回归和神经网络的生物过程区域模型
2006 8th Seminar on Neural Network Applications in Electrical Engineering Pub Date : 2006-09-01 DOI: 10.1109/NEUREL.2006.341209
P. Radonja, S. Stankovic, B. Matović, D. Dražić
{"title":"Regional Models for Biological Processes Based on Linear Regression and Neural Networks","authors":"P. Radonja, S. Stankovic, B. Matović, D. Dražić","doi":"10.1109/NEUREL.2006.341209","DOIUrl":"https://doi.org/10.1109/NEUREL.2006.341209","url":null,"abstract":"In this paper linear regression and neural networks are used for obtaining regional models of biological processes. Regional models enable getting the most important regional characteristics without detailed measurements on all individual objects. Testing of the obtained regional model by using data samples is done. A very high correlation is obtained between real data and data computed on the basis of regional models. It is shown that application of NNs provides better regional models than those obtained by linear regression","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114074117","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
Bee Colony Optimization: Principles and Applications 蜂群优化:原理与应用
2006 8th Seminar on Neural Network Applications in Electrical Engineering Pub Date : 2006-09-01 DOI: 10.1109/NEUREL.2006.341200
D. Teodorovic, P. Lucic, G. Marković, M. D. Orco
{"title":"Bee Colony Optimization: Principles and Applications","authors":"D. Teodorovic, P. Lucic, G. Marković, M. D. Orco","doi":"10.1109/NEUREL.2006.341200","DOIUrl":"https://doi.org/10.1109/NEUREL.2006.341200","url":null,"abstract":"The bee colony optimization metaheuristic (BCO) is proposed in the paper. The BCO represents the new metaheuristic capable to solve difficult combinatorial optimization problems. The artificial bee colony behaves partially alike, and partially differently from bee colonies in nature. In addition to proposing the BCO as a new metaheuristic, we also describe in the paper two BCO algorithms that we call the bee system (BS) and the fuzzy bee system (FBS). In the case of FBS the agents (artificial bees) use approximate reasoning and rules of fuzzy logic in their communication and acting. In this way, the FBS is capable to solve deterministic combinatorial problems, as well as combinatorial problems characterized by uncertainty. The proposed approach is illustrated by three case studies","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114719434","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: 194
On Possible Constraints in Applications of Basic Defuzzification Techniques 基本去模糊化技术应用中的可能约束
2006 8th Seminar on Neural Network Applications in Electrical Engineering Pub Date : 2006-09-01 DOI: 10.1109/NEUREL.2006.341218
D. Saletic, U. Popovic
{"title":"On Possible Constraints in Applications of Basic Defuzzification Techniques","authors":"D. Saletic, U. Popovic","doi":"10.1109/NEUREL.2006.341218","DOIUrl":"https://doi.org/10.1109/NEUREL.2006.341218","url":null,"abstract":"The purpose of this paper is to give the results of research analysis of basic defuzzification techniques and to point out to possible constraints in application of these techniques. The defuzzification process is present in a fuzzy system when an output fuzzy set should be mapped to a crisped value. Features are given which is the base for a defuzzification technique comparison. Techniques are classified into several groups. The analysis of defuzzification techniques is given, as well as their comparison on the base of given features. The results from computer experiments suggest constrained domain of applicability of defuzzification techniques. Suggestions about applicability of techniques in specified applications are given","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129319687","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
Applications of Neural Networks in Network Intrusion Detection 神经网络在网络入侵检测中的应用
2006 8th Seminar on Neural Network Applications in Electrical Engineering Pub Date : 2006-09-01 DOI: 10.1109/NEUREL.2006.341176
A. Lazarevic, D. Pokrajac, J. Nikolic
{"title":"Applications of Neural Networks in Network Intrusion Detection","authors":"A. Lazarevic, D. Pokrajac, J. Nikolic","doi":"10.1109/NEUREL.2006.341176","DOIUrl":"https://doi.org/10.1109/NEUREL.2006.341176","url":null,"abstract":"In this paper, we discuss the applications of multilayer perceptrons for classification of network intrusion detection data characterized by skewed class distributions. We compare several methods for learning from such skewed distributions by manipulating data records. The investigated methods include oversampling, undersampling and generating artificial data records using SMOTE technique. The presented methods are tested on KDDCup99 network intrusion dataset and compared using various classification performance metrics. In addition, the influence of decision margin on recall and misclassification rates is also examined","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125925150","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
On Rotation Invariant Texture Classification Using Two-Grid Coupled CNNs 基于双网格耦合cnn的旋转不变纹理分类
2006 8th Seminar on Neural Network Applications in Electrical Engineering Pub Date : 2006-09-01 DOI: 10.1109/NEUREL.2006.341169
P. Ungureanu, E. David, L. Goras
{"title":"On Rotation Invariant Texture Classification Using Two-Grid Coupled CNNs","authors":"P. Ungureanu, E. David, L. Goras","doi":"10.1109/NEUREL.2006.341169","DOIUrl":"https://doi.org/10.1109/NEUREL.2006.341169","url":null,"abstract":"This paper presents several results of rotation-invariant texture classification using a bank of 2D band-pass CNN filters with approximately circular frequency response. The filters are autonomous two grid coupled CNNs, capable of producing Turing patterns used in the central linear part of their characteristic. The classification performances of the CNN filters are compared with the performances of the ideal circular filters","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117132133","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: 10
Neurobiological aspects of content scanning process in sensory systems 感觉系统中内容扫描过程的神经生物学方面
2006 8th Seminar on Neural Network Applications in Electrical Engineering Pub Date : 2006-09-01 DOI: 10.1109/NEUREL.2006.341198
R. Babic
{"title":"Neurobiological aspects of content scanning process in sensory systems","authors":"R. Babic","doi":"10.1109/NEUREL.2006.341198","DOIUrl":"https://doi.org/10.1109/NEUREL.2006.341198","url":null,"abstract":"Considering neurobiological aspects of visual system in birds and particularly in owls, echolocation in horseshoe bat and well known visual system in primates/humans we present their common features that concerns content scanning capabilities. In that we see various fulfilments of the same evolutionary concept in quite different ecology frames. Proper comparison is given, showing how sophisticated are certain ecologically determined features of particular scanning process, and its relation to the phenomenon of attention, whatever how highly embedded in brain functions. We gave the explanation of neurobiological background of such mechanism","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131373667","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
State of the Art in Nonlinear Dynamical System Identification using Artificial Neural Networks 基于人工神经网络的非线性动力系统辨识研究进展
2006 8th Seminar on Neural Network Applications in Electrical Engineering Pub Date : 2006-09-01 DOI: 10.1109/NEUREL.2006.341187
Nenad Todorovic, Petr Klan
{"title":"State of the Art in Nonlinear Dynamical System Identification using Artificial Neural Networks","authors":"Nenad Todorovic, Petr Klan","doi":"10.1109/NEUREL.2006.341187","DOIUrl":"https://doi.org/10.1109/NEUREL.2006.341187","url":null,"abstract":"This paper covers the state of the art in nonlinear dynamical system identification using artificial neural networks (ANN). The main approaches in the last two decades are presented in unified framework. ANN has unique characteristics, which enable them to model nonlinear dynamical systems. The main problems with the choice of ANN model structure are considered and commonly used identification schemes are proposed. A procedure for derivation of parameter estimation law using Lyapunov synthesis approach, which guarantees stability and convergence of the overall identification scheme, is presented","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"46 Suppl 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114273616","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
Asymmetric and Normalized Cuts for Image Clustering and Segmentation 用于图像聚类和分割的非对称和归一化切割
2006 8th Seminar on Neural Network Applications in Electrical Engineering Pub Date : 2006-09-01 DOI: 10.1109/NEUREL.2006.341163
U. Damnjanovic, E. Izquierdo
{"title":"Asymmetric and Normalized Cuts for Image Clustering and Segmentation","authors":"U. Damnjanovic, E. Izquierdo","doi":"10.1109/NEUREL.2006.341163","DOIUrl":"https://doi.org/10.1109/NEUREL.2006.341163","url":null,"abstract":"Over the last few years spectral clustering has emerged as a powerful model for data partitioning and segmentation. Spectral clustering techniques use eigenvalues and eigenvectors of the matrix representation of a suitable graph representing the original data. In this paper a new spectral clustering method is proposed: the asymmetric cut. It allows extraction of relevant information from a dataset by making just one cut over the database. The approach is tailored to the image classification task where a given image class is to be extracted from an image database containing an unknown number of classes. The main goal of this paper is to show that the proposed technique outperforms standard spectral methods under given circumstances. The technique is compared against the conventional and well-known normalized cut algorithm","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122890027","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
Neural Networks for Online Classification of Hand and Finger Movements Using Surface EMG signals 基于表面肌电信号的手部和手指运动在线分类神经网络
2006 8th Seminar on Neural Network Applications in Electrical Engineering Pub Date : 2006-09-01 DOI: 10.1109/NEUREL.2006.341203
G. Tsenov, A. Zeghbib, F. Palis, N. Shoylev, V. Mladenov
{"title":"Neural Networks for Online Classification of Hand and Finger Movements Using Surface EMG signals","authors":"G. Tsenov, A. Zeghbib, F. Palis, N. Shoylev, V. Mladenov","doi":"10.1109/NEUREL.2006.341203","DOIUrl":"https://doi.org/10.1109/NEUREL.2006.341203","url":null,"abstract":"Myoelectric signals (MES) are the electrical manifestation of muscular contractions and they can be used to create myoelectric prosthesis which is able to function with the amputee's muscle movements. This signal recorded at the surface of the skin of the forearm has been exploited to provide recognition of the movement of the hand and finger movements of healthy subject. The objective of the paper is to describe the identification procedure, based on EMG patterns of forearm activity using various neural networks methods and to make a comparison between different intelligent computational methods of identification, which are used in this work. Then an online algorithm for movement identification and classification that utilises the trained neural networks is presented","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125345745","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: 103
Minor Component Analysis (MCA) Applied to Image Classification in CBIR Systems 小分量分析(MCA)在CBIR图像分类中的应用
2006 8th Seminar on Neural Network Applications in Electrical Engineering Pub Date : 2006-09-01 DOI: 10.1109/NEUREL.2006.341164
M. Jankovic, G. Zajic, V. Radosavljevic, N. Kojić, N. Reljin, M. Rudinac, S. Rudinac, B. Reljin
{"title":"Minor Component Analysis (MCA) Applied to Image Classification in CBIR Systems","authors":"M. Jankovic, G. Zajic, V. Radosavljevic, N. Kojić, N. Reljin, M. Rudinac, S. Rudinac, B. Reljin","doi":"10.1109/NEUREL.2006.341164","DOIUrl":"https://doi.org/10.1109/NEUREL.2006.341164","url":null,"abstract":"A content-based image retrieval system with query image classification prior to retrieving procedure is proposed. Query image is compared to representative patterns of image classes, not to all images from database, accelerating thus initial retrieving step. Such procedure is possible when images from database are grouped into classes with similar content. Classification is performed using minor component (MC) analysis. Since it is expectable that MCs mainly depend on image details, not on an image background, this approach seems to be more efficient than classic CBIR. Minor components may be calculated by using single-layer neural network. The efficiency of proposed system is tested over images from Corel dataset","PeriodicalId":231606,"journal":{"name":"2006 8th Seminar on Neural Network Applications in Electrical Engineering","volume":"117 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129137734","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: 8
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