Literatura académica sobre el tema "Eigenvalue-based detection"
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Artículos de revistas sobre el tema "Eigenvalue-based detection"
Patil, Kishor P., Ashwini S. Lande y Mudassar H. Naikwadi. "A Review on the Evolution of Eigenvalue Based Spectrum Sensing Algorithms for Cognitive Radio". Network Protocols and Algorithms 8, n.º 2 (21 de julio de 2016): 58. http://dx.doi.org/10.5296/npa.v8i2.9349.
Texto completoA.Tag El-Dien, Heba, Rokaia M. Zaki, Mohsen M. Tantawy y Hala M. Abdel-Kader. "Noise Uncertainty Effect on a Modified Two-Stage Spectrum Sensing Technique". Indonesian Journal of Electrical Engineering and Computer Science 1, n.º 2 (1 de febrero de 2016): 341. http://dx.doi.org/10.11591/ijeecs.v1.i2.pp341-348.
Texto completoGe, Zhiqiang y Zhihuan Song. "Process structure change detection by eigenvalue-based method". Computers & Chemical Engineering 35, n.º 2 (febrero de 2011): 284–95. http://dx.doi.org/10.1016/j.compchemeng.2010.05.011.
Texto completoAli, Syed Sajjad, Chang Liu, Jialong Liu, Minglu Jin y Jae Moung Kim. "On the Eigenvalue Based Detection for Multiantenna Cognitive Radio System". Mobile Information Systems 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/3848734.
Texto completoPeng, Ziran y Guojun Wang. "A Novel ECG Eigenvalue Detection Algorithm Based on Wavelet Transform". BioMed Research International 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/5168346.
Texto completoLo, Edisanter. "Hyperspectral anomaly detection based on constrained eigenvalue–eigenvector model". Pattern Analysis and Applications 20, n.º 2 (22 de septiembre de 2015): 531–55. http://dx.doi.org/10.1007/s10044-015-0519-6.
Texto completoDu, Liping, Yuting Fu, Yueyun Chen, Xiaojian Wang y Xiaoyan Zhang. "Eigenvalue-Based Spectrum Sensing with Small Samples Using Circulant Matrix". Symmetry 13, n.º 12 (5 de diciembre de 2021): 2330. http://dx.doi.org/10.3390/sym13122330.
Texto completoYan, Binpeng, Sanyi Yuan, Shangxu Wang, Yonglin OuYang, Tieyi Wang y Peidong Shi. "Improved eigenvalue-based coherence algorithm with dip scanning". GEOPHYSICS 82, n.º 2 (1 de marzo de 2017): V95—V103. http://dx.doi.org/10.1190/geo2016-0149.1.
Texto completoParamo, Gian y Arturo S. Bretas. "WAMs Based Eigenvalue Space Model for High Impedance Fault Detection". Applied Sciences 11, n.º 24 (20 de diciembre de 2021): 12148. http://dx.doi.org/10.3390/app112412148.
Texto completoXu, Huaping, Siyuan Wang, Shuo Li, Guobing Zeng, Zhenwan You y Wei Li. "Multibaseline InSAR Layover Detection Based on Local Frequency and Eigenvalue". IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14 (2021): 10571–82. http://dx.doi.org/10.1109/jstars.2021.3120007.
Texto completoTesis sobre el tema "Eigenvalue-based detection"
TESHOME, ABIY TEREFE. "FPGA based Eigenvalue Detection Algorithm for Cognitive Radio". Thesis, Högskolan i Gävle, Radio Center Gävle, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-7855.
Texto completoJust, Frederick A. "Damage Detection Based on the Geometric Interpretation of the Eigenvalue Problem". Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/29555.
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Ayeh, Eric. "Statistical Strategies for Efficient Signal Detection and Parameter Estimation in Wireless Sensor Networks". Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc407740/.
Texto completoArts, Martijn Verfasser], Rudolf [Akademischer Betreuer] [Mathar y Anja [Akademischer Betreuer] Klein. "Eigenvalue-Based Spectrum Sensing for Cognitive Radio: Change Detection Problems and Fundamental Performance Limits / Martijn Arts ; Rudolf Mathar, Anja Klein". Aachen : Universitätsbibliothek der RWTH Aachen, 2017. http://d-nb.info/1162450436/34.
Texto completoRIVIELLO, DANIEL GAETANO. "Spectrum sensing algorithms and software-defined radio implementation for cognitive radio system". Doctoral thesis, Politecnico di Torino, 2016. http://hdl.handle.net/11583/2641328.
Texto completoKobeissi, Hussein. "Eigenvalue Based Detector in Finite and Asymptotic Multi-antenna Cognitive Radio Systems". Thesis, CentraleSupélec, 2016. http://www.theses.fr/2016SUPL0011/document.
Texto completoIn Cognitive Radio, Spectrum Sensing (SS) is the task of obtaining awareness about the spectrum usage. Mainly it concerns two scenarios of detection: (i) detecting the absence of the Primary User (PU) in a licensed spectrum in order to use it and (ii) detecting the presence of the PU to avoid interference. Several SS techniques were proposed in the literature. Among these, Eigenvalue Based Detector (EBD) has been proposed as a precious totally-blind detector that exploits the spacial diversity, overcome noise uncertainty challenges and performs adequately even in low SNR conditions. The first part of this study concerns the Standard Condition Number (SCN) detector and the Scaled Largest Eigenvalue (SLE) detector. We derived exact expressions for the Probability Density Function (PDF) and the Cumulative Distribution Function (CDF) of the SCN using results from finite Random Matrix Theory; In addition, we derived exact expressions for the moments of the SCN and we proposed a new approximation based on the Generalized Extreme Value (GEV) distribution. Moreover, using results from the asymptotic RMT we further provided a simple forms for the central moments of the SCN and we end up with a simple and accurate expression for the CDF, PDF, Probability of False-Alarm, Probability of Detection, of Miss-Detection and the decision threshold that could be computed and hence provide a dynamic SCN detector that could dynamically change the threshold value depending on target performance and environmental conditions. The second part of this study concerns the massive MIMO technology and how to exploit the large number of antennas for SS and CRs. Two antenna exploitation scenarios are studied: (i) Full antenna exploitation and (ii) Partial antenna exploitation in which we have two options: (i) Fixed use or (ii) Dynamic use of the antennas. We considered the Largest Eigenvalue (LE) detector if noise power is perfectly known and the SCN and SLE detectors when noise uncertainty exists
Knapo, Peter. "Vývoj algoritmů pro digitální zpracování obrazu v reálním čase v DSP procesoru". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217872.
Texto completoCapítulos de libros sobre el tema "Eigenvalue-based detection"
Azmoodeh, Amin, Ali Dehghantanha, Reza M. Parizi, Sattar Hashemi, Bahram Gharabaghi y Gautam Srivastava. "Active Spectral Botnet Detection Based on Eigenvalue Weighting". En Handbook of Big Data Privacy, 385–97. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38557-6_19.
Texto completoMaali, Asmaa, Sara Laafar, Hayat Semlali, Najib Boumaaz y Abdallah Soulmani. "Maximum Eigenvalue Based Detection Using Jittered Random Sampling". En Lecture Notes on Data Engineering and Communications Technologies, 183–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11437-4_14.
Texto completoZhang, Chunjie, Shanshuang Li, Zhian Deng y Yingjun Hao. "An Improved Eigenvalue-Based Channelized Sub-band Spectrum Detection Method". En Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 244–51. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19086-6_27.
Texto completoFeng, Sai-sai, Yue-bin Chen y Fei Gao. "Signal Detection Based on Maximum-Minimum Eigenvalue in Rician Fading Channel". En Lecture Notes in Computer Science, 160–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38227-7_19.
Texto completoGuan, Gangqiang, Deyong Xian, Liu Shi, Jia Mu y Xinshu Zhao. "Analysis of Threshold Setting for Eigenvalue Ratio Based Interference Detection Under Constant Missed Detection Probability". En China Satellite Navigation Conference (CSNC) 2017 Proceedings: Volume I, 997–1007. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4588-2_84.
Texto completoJiang, Jingjing, Xinming Liu, Wenzhuang Chen y Aikun Mao. "Cluster Analysis Based Eigenvalue Extraction and Dynamic Time Regulation for Electricity Anomaly Detection". En Lecture Notes in Electrical Engineering, 1130–38. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1528-4_115.
Texto completoCharan, Chhagan y Rajoo Pandey. "Cooperative Spectrum Sensing Using Eigenvalue-Based Double-Threshold Detection Scheme for Cognitive Radio Networks". En Advances in Intelligent Systems and Computing, 189–99. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1822-1_18.
Texto completoWang, Miao, Xiao-xia Cai y Ke-fan Zhu. "Underdetermined Mixed Matrix Estimation of Single Source Point Detection Based on Noise Threshold Eigenvalue Decomposition". En Lecture Notes in Electrical Engineering, 704–11. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-9409-6_83.
Texto completoElleuch, Ines, Fatma Abdelkefi y Mohamed Siala. "Complexity Issues within Eigenvalue-Based Multi-Antenna Spectrum Sensing". En Advances in Wireless Technologies and Telecommunication, 603–17. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6571-2.ch023.
Texto completoBhatti, Farrukh A., Gerard B. Rowe y Kevin W. Sowerby. "Spectrum Sensing Using Principal Components for Multiple Antenna Cognitive Radios". En Advances in Wireless Technologies and Telecommunication, 179–99. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6571-2.ch007.
Texto completoActas de conferencias sobre el tema "Eigenvalue-based detection"
Maali, Asmaa, Hayat Semlali, Najib Boumaaz y Abdallah Soulmani. "Energy detection versus maximum eigenvalue based detection: A comparative study". En 2017 14th International Multi-Conference on Systems, Signals & Devices (SSD). IEEE, 2017. http://dx.doi.org/10.1109/ssd.2017.8166914.
Texto completoGetu, Tilahun M., Wessam Ajib y Rene Landry. "An Eigenvalue-Based Multi-Antenna RFI Detection Algorithm". En 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall). IEEE, 2018. http://dx.doi.org/10.1109/vtcfall.2018.8690863.
Texto completoZi-li, WANG, SONG Xiao-ou y WANG Xiao-rong. "Spectrum Sensing Detection Algorithm Based on Eigenvalue Variance". En 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC). IEEE, 2019. http://dx.doi.org/10.1109/itaic.2019.8785807.
Texto completoSwamy, Tata Jagannadha, Srinivas Avasarala, Thaskani Sandhya y Garimella Ramamurthy. "Spectrum sensing: Approximations for Eigenvalue ratio based detection". En 2012 International Conference on Computer Communication and Informatics (ICCCI). IEEE, 2012. http://dx.doi.org/10.1109/iccci.2012.6158914.
Texto completoZhengzheng Sun. "On the performance of eigenvalue-based signal detection". En 2012 12th International Conference on ITS Telecommunications (ITST). IEEE, 2012. http://dx.doi.org/10.1109/itst.2012.6425193.
Texto completoYuan Sun, Bo Zhang, Chao Wang y Fan Wu. "Ship detection based on eigenvalue-eigenvector decomposition and OS-CFAR detector". En 2012 International Conference on Computer Vision in Remote Sensing (CVRS). IEEE, 2012. http://dx.doi.org/10.1109/cvrs.2012.6421288.
Texto completoMiranda, Joao Paulo, Boris Galkin, Giuseppe Abreu y Luiz DaSilva. "Experimental assessment of eigenvalue-based detection for cognitive radio". En 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2014. http://dx.doi.org/10.1109/sam.2014.6882364.
Texto completoZhang, Lamei, Bin Zou y Wenyan Tang. "Building detection based on Polarimetric Interferometric Eigenvalue Similarity Parameter". En 2011 IEEE Radar Conference (RadarCon). IEEE, 2011. http://dx.doi.org/10.1109/radar.2011.5960619.
Texto completoWei, Lu y Olav Tirkkonen. "Spectrum sensing with Gaussian approximated eigenvalue ratio based detection". En 2010 7th International Symposium on Wireless Communication Systems (ISWCS 2010). IEEE, 2010. http://dx.doi.org/10.1109/iswcs.2010.5624271.
Texto completoBhagath, Parabattina y Pradip K. Das. "Graph Eigenvalue based Structural Method towards Phonetic Boundary Detection". En TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON). IEEE, 2021. http://dx.doi.org/10.1109/tencon54134.2021.9707281.
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