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Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/7207
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dc.contributor.authorallDecherchi, S.; Dept. Drug Discovery and Development- Italian Institute of Technology, Morego, Genova, Italyen
dc.contributor.authorallLeoncini, D.; Dept. Biophysical and Electronic Eng., University of Genoa, Genova, ITALYen
dc.contributor.authorallGastaldo, P.; Dept. Biophysical and Electronic Eng., University of Genoa, Genova, ITALYen
dc.contributor.authorallZunino, R.; Dept. Biophysical and Electronic Eng., University of Genoa, Genova, ITALYen
dc.contributor.authorallFaggioni, O.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italiaen
dc.contributor.authorallSoldani, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italiaen
dc.date.accessioned2011-11-29T11:17:27Zen
dc.date.available2011-11-29T11:17:27Zen
dc.date.issued2011-07-31en
dc.identifier.urihttp://hdl.handle.net/2122/7207en
dc.description.abstractMagnetic-based detection technologies for undersea protection systems are very effective in monitoring critical areas where weak signal sources are difficult to identify (e.g. diver intrusion in proximity of the seafloor). The complexity of the involved geomagnetic phenomena and the nature of the target detection strategy require the use of adaptive methods for signal processing. The paper shows that Computational Intelligence (CI) models can be integrated with those magnetic-based technologies, and presents an effective, reliable system for adaptive undersea protection. Two different CI paradigms are successfully tested for the specific application task: Circular BackPropagation (CBP) and Support Vector Machines (SVMs). Experimental results on real data prove the advantage of the integrated approach over existing conventional methods. Individual CI components and the overall detection system have been verified in real experiments.en
dc.language.isoEnglishen
dc.publisher.nameInternational Neural Network Society & IEEE Computation Intelligence Societyen
dc.relation.ispartofProceedings of International Joint Conference on Neural Networksen
dc.subjectunderwater detection systemsen
dc.subjectport protectionen
dc.subjectmagnetic signal processingen
dc.subjectSupport Vector Machineen
dc.titleComputational Intelligence Methods for Underwater Magnetic-based Protection Systemsen
dc.typeConference paperen
dc.description.statusPublisheden
dc.subject.INGV04. Solid Earth::04.05. Geomagnetism::04.05.04. Magnetic anomaliesen
dc.subject.INGV04. Solid Earth::04.05. Geomagnetism::04.05.08. Instruments and techniquesen
dc.subject.INGV05. General::05.01. Computational geophysics::05.01.01. Data processingen
dc.subject.INGV05. General::05.01. Computational geophysics::05.01.05. Algorithms and implementationen
dc.description.ConferenceLocationSan Jose, California, USAen
dc.relation.references[1] D. Yao, M.R. Azimi-Sadjadi, A.A. Jamshidi, and G.J. Dobeck, “A study of effects of sonar bandwidth for underwater target classification,” IEEE Journal of Oceanic Engineering, vol. 27, July 2002 pp. 619 - 627 [2] D. Li, M.R. Azimi-Sadjiadi, and M. Robinson, “Comparison of different classification algorithms for underwater target discrimination,” IEEE Transactions on Neural Networks, vol. 15, Jan. 2004, pp. 189-194 [3] M.R. Azimi-Sadjadi, D. Yao, Q. Huang, and G.J. Dobeck, “Underwater target classification using wavelet packets and neural networks,” IEEE Trans. on Neural Networks, vol. 11, May 2000, pp. 784-794 [4] M. R. Azimi-Sadjadi, D. Yao, A.A. Jamshidi, and J.G. Dobeck, “Underwater target classification in changing environments using an adaptive feature mapping,” IEEE Trans. on Neural Networks, vol. 13, Sept. 2002, pp. 1099-1111 [5] R.P. Gorman and T.J. Sejnowski, “Analysis of Hidden Units in a Layered Network Trained to Classify Sonar Targets,” Neural Networks, vol. 1, 1988, pp. 75-89. [6] R.J. Urick. Principles of Underwater Sound. McGraw-Hill (New York), 1983. [7] O. Faggioni, A. Gabellone, R. Hollett, R.T. Kessel, and M. Soldani, “Anti-intruder port protection MAC (Magnetic ACoustic) System: advances in the magnetic component performance,” 1st WSS Conference, August 25-28, Copenhagen, Denmark, 2008. [8] V. Vapnik, Statistical Learning Theory, John Wiley, New York, 1998, pp. 339-346 [9] S. Ridella, S. Rovetta, and R. Zunino, “Circular backpropagation networks for classification,” IEEE Trans. on Neural Networks, vol. 8, no. 1, 1997, , pp. 84-97 [10] A. Gabellone, O. Faggioni, M. Soldani, and P. Guerrini, “CAIMAN (Coastal Anti Intruder MAgnetometers Network),” Proc. of RTO-MPSET- 130 Symposium on NATO Military Sensing, March 12-14, Orlando, Florida, USA, 2008, NATO classified. [11] L.P. Wang and X.J. Fu, Data Mining with Computational Intelligence, Springer, Berlin, 2005. [12] K. Hornik, M. Stinchcombe, and H. White, “Multilayer feedforward networks are universal approximators,” Neural Networks, vol. 2, no. 5, pp. 359–356,1989. [13] S. Dasgupta and A. Gupta, “An elementary proof of the Johnson– Lindenstrauss lemma”, Technical report 99–006, U. C. Berkeley, March 1999. [14] S. Decherchi, P. Gastaldo, and R. Zunino, "K-Means clustering for Content Based Document Management in Intelligence," in Advances In Artificial Intelligence for Privacy Protection and Security, Editors: Augusti Solanas and Antoni Martinez Bellesté, World Scientific Publishing, 2009 [15] D. Leoncini, S. Decherchi, O. Faggioni, P. Gastaldo, M. Soldani, and R. Zunino, “A Preliminary Study on SVM based Analysis of Underwater Magnetic Signals For Port Protection,” Proc. CISIS 2009, Burgos, Spain. [16] C.C.Chang and C.J. Lin, “LibSVM: a library for Support Vector Machines” [http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf]en
dc.description.obiettivoSpecifico1.6. Osservazioni di geomagnetismoen
dc.description.obiettivoSpecifico2.5. Laboratorio per lo sviluppo di sistemi di rilevamento sottomarinien
dc.description.obiettivoSpecifico3.4. Geomagnetismoen
dc.description.fulltextopenen
dc.contributor.authorDecherchi, S.en
dc.contributor.authorLeoncini, D.en
dc.contributor.authorGastaldo, P.en
dc.contributor.authorZunino, R.en
dc.contributor.authorFaggioni, O.en
dc.contributor.authorSoldani, M.en
dc.contributor.departmentDept. Drug Discovery and Development- Italian Institute of Technology, Morego, Genova, Italyen
dc.contributor.departmentDept. Biophysical and Electronic Eng., University of Genoa, Genova, ITALYen
dc.contributor.departmentDept. Biophysical and Electronic Eng., University of Genoa, Genova, ITALYen
dc.contributor.departmentDept. Biophysical and Electronic Eng., University of Genoa, Genova, ITALYen
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italiaen
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italiaen
item.openairetypeConference paper-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
crisitem.author.deptDept. Biophysical and Electronic Engineering, University of Genoa, 16145 Genoa, Italy-
crisitem.author.deptDefence Geophysics Group; University of Genoa, DIBE, SEA Lab, Via All’Opera Pia 11a, 16145 Genova, Italy-
crisitem.author.deptDefence Geophysics Group; University of Genoa, DIBE, SEA Lab, Via All’Opera Pia 11a, 16145 Genova, Italy-
crisitem.author.deptUniversità degli Studi di Genova – DITEN Genova, Italy-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Roma2, Roma, Italia-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Roma2, Roma, Italia-
crisitem.author.orcid0000-0002-9772-3453-
crisitem.author.orcid0000-0001-7039-2781-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.classification.parent04. Solid Earth-
crisitem.classification.parent04. Solid Earth-
crisitem.classification.parent05. General-
crisitem.classification.parent05. General-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
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