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2013 IEEE INISTA最新文献

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An algorithm for error reducing in IMU IMU中的误差减小算法
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577663
K. Alexiev, I. Nikolova
{"title":"An algorithm for error reducing in IMU","authors":"K. Alexiev, I. Nikolova","doi":"10.1109/INISTA.2013.6577663","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577663","url":null,"abstract":"During the last few years microminiaturized inertial sensors were introduced in many applications. Their small size, low power consumption, rugged construction open doors to many areas of implementation. The main drawback of these sensors is gyro drift, leading to an unavoidable accumulation of errors. In the paper an approach is proposed to diminish error accumulation.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123773910","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: 5
Digit recognition in a simplified visual cortex model 基于简化视觉皮层模型的数字识别
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577635
I. C. Cevikbas, T. Yıldırım
{"title":"Digit recognition in a simplified visual cortex model","authors":"I. C. Cevikbas, T. Yıldırım","doi":"10.1109/INISTA.2013.6577635","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577635","url":null,"abstract":"In this paper a simplified visual cortex model is developed and application of the model to digit detection is explored. Retina and Lateral Geniculate Nucleus (LGN) is modeled as a combined 64×64 input cell array. An applied digit pattern produces Poisson spikes at the output of the combined retina-LGN cell array. Retina-LGN cells are connected to primary visual cortex (V1) cell network. Spike rate pattern of any digit applied to the input is used in digit detection.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122476460","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
Tracking applications with fuzzy-based fusion rules 使用基于模糊的融合规则跟踪应用程序
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577630
A. Tchamova, J. Dezert
{"title":"Tracking applications with fuzzy-based fusion rules","authors":"A. Tchamova, J. Dezert","doi":"10.1109/INISTA.2013.6577630","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577630","url":null,"abstract":"The objective of this paper is to present and evaluate the performance of a particular fusion rule based on fuzzy T-Conorm/T-Norm operators for two tracking applications: (1) Tracking Object's Type Changes, supporting the process of identification, (e.g. friendly aircraft against hostile ones, fighter against cargo) and consequently for improving the quality of generalized data association; (2) Alarms identification and prioritization in terms of degree of danger relating to a set of a priori defined, out of the ordinary dangerous directions. The aim is to present and demonstrate the ability of TCN rule to assure coherent and stable way for identification and to improve decision-making process in temporal way. A comparison with performance of DSmT based PCR5 fusion rule and Dempster's rule is also provided.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124075957","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
Cluster analysis for EEG biosignal discrimination 脑电生物信号识别的聚类分析
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577646
O. Georgieva, S. Milanov, P. Georgieva
{"title":"Cluster analysis for EEG biosignal discrimination","authors":"O. Georgieva, S. Milanov, P. Georgieva","doi":"10.1109/INISTA.2013.6577646","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577646","url":null,"abstract":"The paper aims to define the ability of unsupervised learning approach to identify emotional biosignals evoked while viewing affected pictures. Two problems are consequently resolved. First, the most important features of the Electroencephalography (EEG) data set have been selected. Secondly, cluster analysis technique is applied in order to extract the specific knowledge of the existing dependencies. The clustering results of particular data subsets are presented and discussed.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127681367","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
The influence of random numbers generators upon Genetic Algorithms 随机数生成器对遗传算法的影响
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1504/IJRIS.2013.058772
M. Olteanu, N. Paraschiv
{"title":"The influence of random numbers generators upon Genetic Algorithms","authors":"M. Olteanu, N. Paraschiv","doi":"10.1504/IJRIS.2013.058772","DOIUrl":"https://doi.org/10.1504/IJRIS.2013.058772","url":null,"abstract":"Genetic Algorithms represent a technique of Artificial Intelligence which has developed from the paradigm of biological evolution. They use a population of potential solutions which gradually evolve toward the best solution which satisfies an objective function. By their nature, Genetic Algorithms use random numbers. In a typical algorithm running, a random number generator is used in many occasions, like selection of the best individuals, choosing the parents for crossover and actually applying crossover, and in mutation. Relying on a standard algorithm for random numbers has the advantage of simplicity and easy implementation (for example in embedded applications), but the quality of the random numbers could influence the final results. In this paper we investigate the effect of the random number generator used by a genetic algorithm in finding the optimal solution for two test functions.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116164761","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
Performance evaluation of feature selection algorithms on human activity classification 特征选择算法在人体活动分类中的性能评价
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577634
Gokalp Tulum, N. T. Artug, B. Bolat
{"title":"Performance evaluation of feature selection algorithms on human activity classification","authors":"Gokalp Tulum, N. T. Artug, B. Bolat","doi":"10.1109/INISTA.2013.6577634","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577634","url":null,"abstract":"In this work, four human activities were classified by using multi layer perceptron and k-nearest neighbours algorithm. Due to mass amount of data, two different feature selection methods, which are ReliefF and t-score, were applied to the data. The best result is obtained as 97.6% with 51 features selected by ReliefF.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123058187","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
Extending nonmonotonic description logic with temporal aspects 用时间方面扩展非单调描述逻辑
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577615
Ouarda Bettaz, Narhimène Boustia, A. Mokhtari
{"title":"Extending nonmonotonic description logic with temporal aspects","authors":"Ouarda Bettaz, Narhimène Boustia, A. Mokhtari","doi":"10.1109/INISTA.2013.6577615","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577615","url":null,"abstract":"This paper is about extending nonmonotonic description logic with temporal aspects; this attempt permits actually to represent both default and temporal features in concepts definition. The introduction of defaults in the definition of concepts in previous researches has allowed to go beyond the strict limitations on their description and permitted consequently to fully define them; by providing both necessary and sufficient conditions for their representation. This allowed improving the classification process. Contrary to the use of strict knowledge that provides only necessary conditions leaving the concepts partially defined. The nonmonotonic language that allows using defaults in the definition of concepts is AL augmented with default and exception connectors that allow respectively representing default and exception properties in concepts definition. However we frequently need to add the temporal aspect to the nonmonotonic feature as it is the case in causal reasoning, planning process, and action theory. In our case, we will use it in the field of access control. Our aim in this paper is to extend this logic further with temporal connectives to grant the possibility to represent temporal properties of concepts and that by referring to temporal description logic.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129644299","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: 5
A novel method for software effort estimation: Estimating with boundaries 一种新的软件工作量估算方法:边界估算
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577643
Omer Faruk Sarac, N. Duru
{"title":"A novel method for software effort estimation: Estimating with boundaries","authors":"Omer Faruk Sarac, N. Duru","doi":"10.1109/INISTA.2013.6577643","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577643","url":null,"abstract":"Software effort estimation is a crucial phase in software project management. Accuracy of estimation directly affects project success or failure. Managers try to estimate proper effort resources and this is a challenging issue for management. Having a set of tools and methodologies, estimation process can be made better. COCOMO is one of the most used model which has a parametric form. Also, artificial neural networks (ANN) are combined with COCOMO and these methods increased overall performance. However, effort estimation process generally produces one output; estimation value. It is a well-known issue that a project manager must keep in the mind that any estimation must have some upper and lower limits, boundaries. In this paper, a novel method, combining COCOMO used ANN with K-Means is used to estimate effort and possible boundaries. ANN output is used as input to K-Means sets and proper set value is calculated, including possible lower and upper effort estimation value. Experimental results are shown that proposed method has acceptable results over ANN and COCOMO.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129690661","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: 12
Clustering of spectral images using Echo state networks 基于回声状态网络的光谱图像聚类
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577633
P. Koprinkova-Hristova, D. Angelova, D. Borisova, G. Jelev
{"title":"Clustering of spectral images using Echo state networks","authors":"P. Koprinkova-Hristova, D. Angelova, D. Borisova, G. Jelev","doi":"10.1109/INISTA.2013.6577633","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577633","url":null,"abstract":"In the present work we applied a recently developed procedure for multidimensional data clustering to processing of spectral satellite images. The core of our approach lays in projection of multidimensional image to a two dimensional one. The main aim is to discover points with similar characteristics. This was done by clustering of the resulting image. The processing technique exploits equilibrium states of a kind of recurrent neural network - Echo state network (ESN) - that are obtained after intrinsic plasticity (IP) tuning of the ESN using multidimensional data as inputs. The proposed in our previous work automated procedure for multidimensional data clustering is further refined and tested on the satellite image data. The obtained number and position of clusters of a multi-spectral image of a mountain region in Bulgaria is compared with the classification of the region landscape given by the Ministry of Regional Development and Public Works.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134285112","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: 14
Index matrix interpretation of the Multilayer perceptron 多层感知器的指标矩阵解释
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577637
K. Atanassov, S. Sotirov
{"title":"Index matrix interpretation of the Multilayer perceptron","authors":"K. Atanassov, S. Sotirov","doi":"10.1109/INISTA.2013.6577637","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577637","url":null,"abstract":"Neural networks are a mathematical model for solving problems, that uses the structure of human brain. One of the mostly used kinds of neural networks, the Multilayer perceptron (MLP), has been modelled with various tools. Here, starting with the MLP, we approach the problem by modelling neural networks in terms of index matrices (IMs). The work includes IM interpretations of the building components of the neural network, namely, input vector, weight coefficients, transfer function, and biases, as well as the various operations defined over these.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132143016","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
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