A. Refenes, F. Blayo, Magali E. Azema-Barac, D. Bounds, G. Grudnitski, D. Ross
{"title":"Economics, Finance, and Business","authors":"A. Refenes, F. Blayo, Magali E. Azema-Barac, D. Bounds, G. Grudnitski, D. Ross","doi":"10.1201/9781420050646.PTG6","DOIUrl":"https://doi.org/10.1201/9781420050646.PTG6","url":null,"abstract":"","PeriodicalId":165433,"journal":{"name":"Handbook of Fuzzy Computation","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128266136","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}
Enrique H. Ruspini, Piero P Bonissone, Witold Pedrycz
{"title":"Aerospace","authors":"Enrique H. Ruspini, Piero P Bonissone, Witold Pedrycz","doi":"10.2307/3959140","DOIUrl":"https://doi.org/10.2307/3959140","url":null,"abstract":"Ultra-tight integration Tracking error In the traditional strapdown inertial navigation system/global positioning system (SINS/GPS) ultra-tight integration structure, the mutual aiding between SINS and GPS forms a positive feedback loop, through which measurement errors of both subsystems are coupled deeply. In signal jamming or/and dynamic conditions, the Doppler aiding error derived from the SINS using low-grade inertial measurement unit (IMU) can increase rapidly, and cause GPS measurement errors to be correlated with the SINS velocity errors. Such correlations can result in poor estimation accuracy of the integration Kalman filter, losing lock of tracking loops or even yielding system instability. To solve this problem, we propose to model tracking errors of the SINS aided phase lock loop and to derive a new tracking-error estimator. Then, an innovative scheme for SINS/GPS ultra-tight integration using low-grade IMU is investigated. Simulations experiments are implemented to verify this innovative scheme under challenging environments.","PeriodicalId":165433,"journal":{"name":"Handbook of Fuzzy Computation","volume":"7 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141224386","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}
{"title":"Knowledge-Based Systems","authors":"Enrique H. Ruspini, P. Bonissone, Witold Pedrycz","doi":"10.1201/9780429142741-79","DOIUrl":"https://doi.org/10.1201/9780429142741-79","url":null,"abstract":"Multi-view unsupervised feature selection (MUFS) has recently aroused considerable attention, which can select the compact representative feature subset from original multi-view data. Despite the promising preliminary performance, most previous MUFS methods fail to explore the discriminative ability of multi-view data. In addition, they usually utilize spectral analysis to maintain the geometrical structure, which will inevitably increase the difficulty of parameter selection. To address these issues, we present a novel MUFS method, named structural regularization based discriminative multi-view unsupervised feature selection (SDFS). Specifically, we calculate the similarity matrix of sample space from different views and automatically weight each view-specific graph to learn a consensus similarity graph, in which these two types of graphs can promote each other. Further, we treat the learned latent representation as the cluster indicator, and employ a graph regularization without introducing additional parameters to maintain the geometrical structure of data. Besides, a simple yet efficient iterative updating algorithm with theoretical convergence property is developed. Extensive experiments on several benchmark datasets verify that the designed model is superior to several state-of-the-art MUFS models.","PeriodicalId":165433,"journal":{"name":"Handbook of Fuzzy Computation","volume":"7 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141224387","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}
{"title":"Directions for Future Research","authors":"","doi":"10.1201/9780429142741-160","DOIUrl":"https://doi.org/10.1201/9780429142741-160","url":null,"abstract":"","PeriodicalId":165433,"journal":{"name":"Handbook of Fuzzy Computation","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116518858","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}
{"title":"Modeling and Simulation","authors":"G. Klir, Bo Yuan","doi":"10.1201/9780429142741-39","DOIUrl":"https://doi.org/10.1201/9780429142741-39","url":null,"abstract":"","PeriodicalId":165433,"journal":{"name":"Handbook of Fuzzy Computation","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117186391","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}
{"title":"Information Science","authors":"A. Debons","doi":"10.1201/9780429142741-149","DOIUrl":"https://doi.org/10.1201/9780429142741-149","url":null,"abstract":"Information science considers the relationships between people, places and technology and the information those interactions yield. The internet is a broad example of a socio-technical system that is comprised of hardware and software, but in daily life is better understood as a constantly changing social infrastructure upon which complex forms of human-human and human-information interaction rest. Scholars and students of information science develop new methods to study these socio-technical phenomena, and translate those findings to the design and development of useful and meaningful technology.","PeriodicalId":165433,"journal":{"name":"Handbook of Fuzzy Computation","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114992757","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}
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