Academic literature on the topic 'Chaos Detection'
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Journal articles on the topic "Chaos Detection":
Fraser, Andrew M. "Chaos and detection." Physical Review E 53, no. 5 (May 1, 1996): 4514–23. http://dx.doi.org/10.1103/physreve.53.4514.
VIBE, KARIN, and JEAN-MARC VESIN. "ON CHAOS DETECTION METHODS." International Journal of Bifurcation and Chaos 06, no. 03 (March 1996): 529–43. http://dx.doi.org/10.1142/s0218127496000230.
Cai, Ming Shan. "Weak Signal Detection Principle Based on Chaotic Duffing Oscillator and its Simulation Method." Advanced Materials Research 108-111 (May 2010): 834–37. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.834.
Setoudeh, Farbod, Ali Khaki Sedigh, and Mohsen Najafi. "A Novel Method for Chaos Detection in Heavy Noisy Environments Based on Distribution of Energy." International Journal of Bifurcation and Chaos 29, no. 13 (December 10, 2019): 1950179. http://dx.doi.org/10.1142/s0218127419501797.
Wu, Dan Hui, and Xin Wu. "Research on the Influence of Noise to Weak Signal Detection Based on Duffing Equation." Applied Mechanics and Materials 65 (June 2011): 5–8. http://dx.doi.org/10.4028/www.scientific.net/amm.65.5.
Cheng, Feng Qin, and Yao Wu Shi. "Random Phase Weak Sine Signal Detection Based on Autocorrelation and Chaos Theory." Applied Mechanics and Materials 397-400 (September 2013): 2129–33. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.2129.
Manas Kumar Yogi. "Investigating the Scope of Chaos Theory for Cyber Threat Detection." Journal of Trends in Computer Science and Smart Technology 5, no. 3 (September 2023): 266–83. http://dx.doi.org/10.36548/jtcsst.2023.3.004.
Haykin, S., and Xiao Bo Li. "Detection of signals in chaos." Proceedings of the IEEE 83, no. 1 (1995): 95–122. http://dx.doi.org/10.1109/5.362751.
Mohammed, Sarah Sabah, and Maher K. Mahmood Al-Azawi. "Performance comparison of some weak signal detection techniques." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 2 (May 1, 2022): 732. http://dx.doi.org/10.11591/ijeecs.v26.i2.pp732-742.
Chang, Shun-Chang. "Stability, Chaos Detection, and Quenching Chaos in the Swing Equation System." Mathematical Problems in Engineering 2020 (December 23, 2020): 1–12. http://dx.doi.org/10.1155/2020/6677084.
Dissertations / Theses on the topic "Chaos Detection":
Schneider, Judith. "Dynamical structures and manifold detection in 2D and 3D chaotic flows." Phd thesis, [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=973637420.
Engler, Joseph John. "Characterization of normality of chaotic systems including prediction and detection of anomalies." Diss., University of Iowa, 2011. https://ir.uiowa.edu/etd/961.
Xu, Yanjun. "Modulation and detection schemes based on chaotic attractors properties : application to wideband transmissions." Toulouse, INSA, 2009. http://eprint.insa-toulouse.fr/archive/00000278/.
In the past twenty years, chaos-based communication systems have been studied, considering the possibility of generating wideband signals by simple electronic circuits, hence low complexity in transceiver. The aim of this thesis is to study the chaos-based wideband transmission systems relying on the properties of chaotic attractors. Firstly, a dynamical system is selected and studied, allowing to generate the chaotic signals with a periodic component. The analysis of such chaotic cyclic attractors (CCA) shows the specific properties. Then, two CCA-based modulation schemes are proposed, with the simple noncoherent detections realized by observing the specific properties of the received signals. The performance evaluation of CCA-based systems in the additive white Gaussian noise (AWGN) channel shows a better noise performance with long symbol duration, compared to the one of differentially chaos shift keying (DCSK). In addition, they have a comparable multipath performance in the 2. 4 GHz ISM environment
Ghosh, Dastidar Samanwoy. "Models of EEG data mining and classification in temporal lobe epilepsy: wavelet-chaos-neural network methodology and spiking neural networks." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180459585.
Ismail, Ali Rida. "Commensurable and Chaotic Nano-Contact Vortex Oscillator (NCVO) study for information processing." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0003.
The amount of data used in information technology is increasing dramatically. This comes with the proliferation of highly advanced electronic technologies. The thermal issues, rising as an effect of such large data processes, impose the usage of novel technologies and paradigms in place of CMOS circuits. Spintronic devices are one of many alternatives proposed so far in the literature. In this work, we consider a spintronic device called nano-contact vortex oscillator (NCVO), which has recently begun to gain attention due to its rich and variable dynamics. This oscillators is operated by an bias DC current and subjected in a magnetic field, that determines it output dynamics. The practical use of the NCVO requires the existence of an accurate model that imitates its output magnetization and the vortex's trajectory rotating around the center in the upper layer of the device. These two variables are needed for the calculation of the equivalent resistance of the NCVO. For that, we build in this PhD work a model for the NCVO producing these two variables using a reservoir computing approach called conceptor-driven network. The network is trained on NCVO data gained by micromagnetic simulation. The built model successfully captures the NCVO dynamics in its different regimes (chaotic, periodic, and quasi- periodic) with an easy shift between regimes. The same network is used then for the detection of chaos in the input-times series. The proposed chaos-detection method has shown to be efficient and more robust compared to existing methods. Finally, the NCVO model is exploited for truly random number generation (TRNG) where a hardware design, fed by a chaotic signal generated by the model, is proposed. This design has shown the ability to compete existing RNG techniques in terms of speed, cost, and quality
Bzikha, Ihssane. "Comparison and development of advanced wiring fault detection methods on coaxial cables." Thesis, Limoges, 2019. http://www.theses.fr/2019LIMO0119.
In this thesis, we present new approaches of soft fault detection and location in simple andcomplex wire networks. The idea is to find a new approach to overcome the difficulties withstandard reflectometry techniques. We prove that before applying post-treatment methods,denoising techniques should be applied, such as empirical mode decomposition (EMD), localmean decomposition (LMD), or the discrete wavelet transform (DWT). These three methodsdecompose a signal into multiple levels to threshold them before signal reconstruction.Testing several applications shows that EMD is the most efficient method, although it hassome limitations as side effects. After the denoising step, the wiring faults can be detected.Time–frequency analysis is employed at this step. This approach, based on the FourierTransform, is able to detect wiring faults only if the noise level is low. To overcome thisdifficulty, the Bayesian approach is beneficial when system complexity increases. Its responseis based on estimation of prior parameters and prior distributions. In this work, the Bayesianapproach is applied via a formal mathematical study followed by simulation results validatingthe proposed approach, with analysis of the parameters that affect the method’s performance.In the domain of soft fault location, we derive a chaos time domain reflectometry approachbased on chaotic signal properties. Our simulation and experimental results prove that thismethod can synthesize signals and localize the soft fault position without the need forsupplemental methods
Halimi, Meriem. "Observation et détection de modes pour la synchronisation des systèmes chaotiques : une approche unifiée." Electronic Thesis or Diss., Université de Lorraine, 2013. http://www.theses.fr/2013LORR0182.
The work developed in this manuscript addresses the synchronization of chaotic systems. It is organized around two main axes: the observer synthesis and the mode detection. In a first step, we recall the main architectures of chaotic encryption systems and show how chaotic systems with polynomial nonlinearities or switched affine dynamics can be rewritten in a polytopic LPV form. A review of the main LMI based results for polytopic LPV observers synthesis is made. An extension to polytopic unknown input observers, both in the deterministic case and noisy or uncertain case, is proposed. These observers ensure chaos synchronization and information recovering in the framework of the following encryption systems: "parametric modulation", "chaotic switching", "two channels transmission" and "inclusion encryption". For affine switched systems used as a generator of chaos, the case where the discrete state is not available is considered. A unified presentation of mode detection methods based on parity spaces proposed in the literature for linear and affine switched discrete time systems is proposed. The problem of discernibility is the subject of a complete study. An approach to estimate time varying delays for affine switched discrete time systems, formulated in terms of mode detection, is proposed as a solution for delay injection encryption
Navarro, Xavier. "Analysis of cerebral and respiratory activity in neonatal intensive care units for the assessment of maturation and infection in the early premature infant." Phd thesis, Université Rennes 1, 2013. http://tel.archives-ouvertes.fr/tel-00979727.
Halimi, Meriem. "Observation et détection de modes pour la synchronisation des systèmes chaotiques : une approche unifiée." Phd thesis, Université de Lorraine, 2013. http://tel.archives-ouvertes.fr/tel-00942426.
Chao, Chengchung [Verfasser]. "Automatic Ultra Wideband Radar System for Life Detection of Hidden Humans / Chengchung Chao." Kiel : Universitätsbibliothek Kiel, 2012. http://d-nb.info/1028798881/34.
Books on the topic "Chaos Detection":
Skokos, Charalampos, Georg A. Gottwald, and Jacques Laskar, eds. Chaos Detection and Predictability. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48410-4.
Killough, Lee. Bridling chaos. Decatur, GA: MM Pub., 1998.
Richards, Justin. The chaos code. New York: Bloomsbury Children's Books, 2007.
Garcia, Kami. Agent of chaos. New York: Imprint, 2017.
Drake, Nick. Egypt: The book of chaos. New York: HarperCollins, 2011.
Drake, Nick. Egypt: The book of chaos. London: Bantam, 2011.
Ruby, Laura. The chaos king. New York, NY: Eos, 2007.
Dell, Shannon. Chaos of crime. New York: Morrow, 1985.
Dell, Shannon. Chaos of crime. London: Gollancz, 1986.
Dell, Shannon. Chaos of crime. New York: Morrow, 1985.
Book chapters on the topic "Chaos Detection":
Parlitz, Ulrich. "Estimating Lyapunov Exponents from Time Series." In Chaos Detection and Predictability, 1–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48410-4_1.
Lega, Elena, Massimiliano Guzzo, and Claude Froeschlé. "Theory and Applications of the Fast Lyapunov Indicator (FLI) Method." In Chaos Detection and Predictability, 35–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48410-4_2.
Barrio, Roberto. "Theory and Applications of the Orthogonal Fast Lyapunov Indicator (OFLI and OFLI2) Methods." In Chaos Detection and Predictability, 55–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48410-4_3.
Cincotta, Pablo M., and Claudia M. Giordano. "Theory and Applications of the Mean Exponential Growth Factor of Nearby Orbits (MEGNO) Method." In Chaos Detection and Predictability, 93–128. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48410-4_4.
Skokos, Charalampos, and Thanos Manos. "The Smaller (SALI) and the Generalized (GALI) Alignment Indices: Efficient Methods of Chaos Detection." In Chaos Detection and Predictability, 129–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48410-4_5.
Sándor, Zsolt, and Nicolás Maffione. "The Relative Lyapunov Indicators: Theory and Application to Dynamical Astronomy." In Chaos Detection and Predictability, 183–220. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48410-4_6.
Gottwald, Georg A., and Ian Melbourne. "The 0-1 Test for Chaos: A Review." In Chaos Detection and Predictability, 221–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48410-4_7.
Siegert, Stefan, and Holger Kantz. "Prediction of Complex Dynamics: Who Cares About Chaos?" In Chaos Detection and Predictability, 249–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48410-4_8.
Skokos, Charalampos, Georg A. Gottwald, and Jacques Laskar. "Erratum to: Chaos Detection and Predictability." In Chaos Detection and Predictability, E1. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48410-4_9.
Celik, Elif Tuba, and Alexandru Serbanescu. "Applications of Transient Signals Detection Using Recurrence Plot Analysis." In Chaos and Complex Systems, 201–7. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33914-1_25.
Conference papers on the topic "Chaos Detection":
Leung, Henry. "Iceberg detection using chaos." In SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, edited by Louis M. Pecora. SPIE, 1993. http://dx.doi.org/10.1117/12.162684.
GAILEY, PAUL C., LEE M. HIVELY, and VLADIMIR A. PROTOPOPESCU. "ROBUST DETECTION OF DYNAMICAL CHANGE IN SCALP EEG." In 5th Experimental Chaos Conference. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812811516_0017.
DOLAN, KEVIN, ALEXANDER NEIMAN, FRANK MOSS, MARK L. SPANO, and ANNETTE WITT. "DETECTION OF UNSTABLE PERIODIC ORBITS IN NOISY DATA, AND CHOOSING THE RIGHT SURROGATES." In 5th Experimental Chaos Conference. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812811516_0018.
Haiping Wu, Wenwu Liu, Jingjun Lou, and Xiaoqiang Wang. "Application of chaos in sonar detection." In 2011 Second International Conference on Mechanic Automation and Control Engineering (MACE). IEEE, 2011. http://dx.doi.org/10.1109/mace.2011.5988079.
du, weibiao, Qinglin Niu, Xingdong Bao, Zhenhua Wang, and Hongxia Mao. "A plume infrared radiation uncertainty evaluation model based on non-intrusive polynomial chaos." In Imaging Detection and Target Recognition, edited by Jiangtao Xu and Chao Zuo. SPIE, 2024. http://dx.doi.org/10.1117/12.3013097.
Mann, I. "Poincare maps and pitch detection in speech." In IEE Colloquium on Signals, Systems and Chaos. IEE, 1997. http://dx.doi.org/10.1049/ic:19971372.
Huang, Yu, Pei Zhou, and Nianqiang Li. "Chaos synchronization in optically pumped quantum-dot spin-VCSELs." In Seventh Symposium on Novel Photoelectronic Detection Technology and Application 2020, edited by Junhao Chu, Qifeng Yu, Huilin Jiang, and Junhong Su. SPIE, 2021. http://dx.doi.org/10.1117/12.2587358.
Li Jingsheng, Wang Wenguang, Sun Jinping, and Mao Shiyi. "Chaos-based target detection from sea clutter." In IET International Radar Conference 2009. IET, 2009. http://dx.doi.org/10.1049/cp.2009.0230.
Wu, Yaojun, and Baoqi Tao. "Detection of chaos based on wavelet transform." In SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, edited by Michael A. Unser, Akram Aldroubi, and Andrew F. Laine. SPIE, 1996. http://dx.doi.org/10.1117/12.255303.
Hongsheng Su and Feng Zhao. "Chaos Detection Method for Power Quality Disturbance." In 2006 6th World Congress on Intelligent Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/wcica.2006.1713340.
Reports on the topic "Chaos Detection":
Chow, Weng Wah Dr, .), Sebastian Maciej Wieczorek, and Geoffrey Kenneth Torrington. LDRD final report on using chaos for ultrasensitive coherent signal detection. Office of Scientific and Technical Information (OSTI), November 2006. http://dx.doi.org/10.2172/899374.
Perdigão, Rui A. P. New Horizons of Predictability in Complex Dynamical Systems: From Fundamental Physics to Climate and Society. Meteoceanics, October 2021. http://dx.doi.org/10.46337/211021.
Sperry, Benjamin, Bradley Sartain, Kurt Getsinger, Brianna Fernando, Kaytee Pokrzywinski, West Bishop, and Mark Heilman. Field demonstration of a peroxide-based algaecide for harmful algal bloom control in Lake Okeechobee. Engineer Research and Development Center (U.S.), September 2023. http://dx.doi.org/10.21079/11681/47624.