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dc.contributor.authorLi, Shih-Yuen_US
dc.contributor.authorYang, Cheng-Hsiungen_US
dc.contributor.authorKo, Li-Weien_US
dc.contributor.authorLin, Chin-Tengen_US
dc.contributor.authorGe, Zheng-Mingen_US
dc.date.accessioned2014-12-08T15:30:30Z-
dc.date.available2014-12-08T15:30:30Z-
dc.date.issued2013en_US
dc.identifier.issn1085-3375en_US
dc.identifier.urihttp://hdl.handle.net/11536/21787-
dc.identifier.urihttp://dx.doi.org/10.1155/2013/909721en_US
dc.description.abstractWe expose the chaotic attractors of time-reversed nonlinear system, further implement its behavior on electronic circuit, and apply the pragmatical asymptotically stability theory to strictly prove that the adaptive synchronization of given master and slave systems with uncertain parameters can be achieved. In this paper, the variety chaotic motions of time-reversed Lorentz system are investigated through Lyapunov exponents, phase portraits, and bifurcation diagrams. For further applying the complex signal in secure communication and file encryption, we construct the circuit to show the similar chaotic signal of time-reversed Lorentz system. In addition, pragmatical asymptotically stability theorem and an assumption of equal probability for ergodic initial conditions (Ge et al., 1999, Ge and Yu, 2000, and Matsushima, 1972) are proposed to strictly prove that adaptive control can be accomplished successfully. The current scheme of adaptive control-by traditional Lyapunov stability theorem and Barbalat lemma, which are used to prove the error vector-approaches zero, as time approaches infinity. However, the core question-why the estimated or given parameters also approach to the uncertain parameters-remains without answer. By the new stability theory, those estimated parameters can be proved approaching the uncertain values strictly, and the simulation results are shown in this paper.en_US
dc.language.isoen_USen_US
dc.titleImplementation on Electronic Circuits and RTR Pragmatical Adaptive Synchronization: Time-Reversed Uncertain Dynamical Systems' Analysis and Applicationsen_US
dc.typeArticleen_US
dc.identifier.doi10.1155/2013/909721en_US
dc.identifier.journalABSTRACT AND APPLIED ANALYSISen_US
dc.contributor.department機械工程學系zh_TW
dc.contributor.department生物科技學系zh_TW
dc.contributor.department電控工程研究所zh_TW
dc.contributor.department腦科學研究中心zh_TW
dc.contributor.departmentDepartment of Mechanical Engineeringen_US
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.contributor.departmentBrain Research Centeren_US
dc.identifier.wosnumberWOS:000316884400001-
dc.citation.woscount1-
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