2012 IEEE 6th International Conference on Information and Automation for Sustainability最新文献

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Novel two dimensional discrete chaotic maps and simulations 新颖的二维离散混沌映射与仿真
Pei Li, L. Min, Yu Hu, Geng Zhao, Xiaodong Li
{"title":"Novel two dimensional discrete chaotic maps and simulations","authors":"Pei Li, L. Min, Yu Hu, Geng Zhao, Xiaodong Li","doi":"10.1109/ICIAFS.2012.6419897","DOIUrl":"https://doi.org/10.1109/ICIAFS.2012.6419897","url":null,"abstract":"This paper introduces one new novel 2-dimensional quadric polynomial discrete chaotic map and seven novel triangle function combination discrete chaotic maps (2D-TFCDM). The 2D-TFCDMs have at least one positive Lyapunov exponent. Extensive numerical simulations display the orbits of the 2D-TFCDMs to have different chaotic attractors.","PeriodicalId":151240,"journal":{"name":"2012 IEEE 6th International Conference on Information and Automation for Sustainability","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117273714","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
Propagation constraints in elephant localization using an acoustic sensor network 基于声传感器网络的大象定位传播约束
Chinthaka M. Dissanayake, R. Kotagiri, M. Halgamuge, Bill Moran, P. Farrell
{"title":"Propagation constraints in elephant localization using an acoustic sensor network","authors":"Chinthaka M. Dissanayake, R. Kotagiri, M. Halgamuge, Bill Moran, P. Farrell","doi":"10.1109/ICIAFS.2012.6419889","DOIUrl":"https://doi.org/10.1109/ICIAFS.2012.6419889","url":null,"abstract":"In this paper we discuss elephant localization framework using acoustic sensor network. We further analyze the effect of various meteorological parameters in elephant vocalization propagation and their consequential effects on elephant positioning accuracy. In addition, we present the effect of signal-to-noise ratio (SNR) on detection of vocalization signal which consequently affects the localization accuracy. Extensive simulation results reviled that the uniform distribution of the temperature throughout the localization area does not defect the localization accuracy. Our results show that temperature variations between sensors and wind velocity and direction have significant effect on positioning accuracy of the system. Regardless of this, it is revealed that the localization accuracy decreases enormously once the SNR level fall under certain marginal level.","PeriodicalId":151240,"journal":{"name":"2012 IEEE 6th International Conference on Information and Automation for Sustainability","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124365883","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: 15
Localization with ghost elimination of emitters via time-delay-of-arrival measurements 通过到达时延测量来消除发射器的鬼影定位
Siriyama Kanthi Herath, P. Pathirana, B. T. Champion, S. Ekanayake
{"title":"Localization with ghost elimination of emitters via time-delay-of-arrival measurements","authors":"Siriyama Kanthi Herath, P. Pathirana, B. T. Champion, S. Ekanayake","doi":"10.1109/ICIAFS.2012.6419928","DOIUrl":"https://doi.org/10.1109/ICIAFS.2012.6419928","url":null,"abstract":"This paper investigates the theoretical requirements for unique localization of multiple emitters using time delay of arrival (TDoA) subjected to the data-association problem. Specifically, an examination is carried out to find the necessary fundamental requirements to solve the so-called ghost node problem pertaining to sensor arrays.","PeriodicalId":151240,"journal":{"name":"2012 IEEE 6th International Conference on Information and Automation for Sustainability","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128921426","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
Application of growing self-organizing map to distinguish between finger tapping and non tapping from brain images 应用生长自组织图从脑图像中区分手指敲击和非敲击
Pin Huang, P. Pathirana, D. Alahakoon, P. Brotchie
{"title":"Application of growing self-organizing map to distinguish between finger tapping and non tapping from brain images","authors":"Pin Huang, P. Pathirana, D. Alahakoon, P. Brotchie","doi":"10.1109/ICIAFS.2012.6419909","DOIUrl":"https://doi.org/10.1109/ICIAFS.2012.6419909","url":null,"abstract":"Growing self-organizing map (GSOM) has been characterized as a knowledge discovery visualization application which outshines the traditional self-organizing map (SOM) due to its dynamic structure in which nodes can grow based on the input data. GSOM is utilized as a visualization tool in this paper to cluster fMRI finger tapping and non- tapping data, demonstrating the visualization capability to distinguish between tapping or non-tapping. A unique feature of GSOM is a parameter called the spread factor whose functionality is to control the spread of the GSOM map. By setting different levels of spread factor, different granularities of region of interests within tapping or non-tapping images can be visualized and analyzed. Euclidean distance based similarity calculation is used to quantify the visualized difference between tapping and non tapping images. Once the differences are identified, the spread factor is used to generate a more detailed view of those regions to provide a better visualization of the brain regions.","PeriodicalId":151240,"journal":{"name":"2012 IEEE 6th International Conference on Information and Automation for Sustainability","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126950414","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
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