Articoli di riviste: "Chaos Detection"

1

Fraser, Andrew M. "Chaos and detection". Physical Review E 53, n. 5 (1 maggio 1996): 4514–23. http://dx.doi.org/10.1103/physreve.53.4514.

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VIBE, KARIN, e JEAN-MARC VESIN. "ON CHAOS DETECTION METHODS". International Journal of Bifurcation and Chaos 06, n. 03 (marzo 1996): 529–43. http://dx.doi.org/10.1142/s0218127496000230.

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Abstract (sommario):

Reliable chaos detection in real-world time series is attracting increasing attention in the scientific community. This work shows that it is possible to use chaos analysis methods such as attractor dimension estimation, Lyapunov exponents estimation and nonlinear prediction, under the condition that the limitations and drawbacks of the algorithms used are kept in mind. Three existing algorithms for chaos characterization are analyzed in terms of classification performances and robustness with respect to noise and data length. It is shown that all three help detect chaos and even classify different types of signals, but that their results are not devoid of ambiguity. An illustrative example is given, in which the algorithms presented are applied to heart rate variability signals, and directions of research are proposed for the design of a straightforward and simple chaos detection methodology.

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Cai, Ming Shan. "Weak Signal Detection Principle Based on Chaotic Duffing Oscillator and its Simulation Method". Advanced Materials Research 108-111 (maggio 2010): 834–37. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.834.

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Based on Matlab as the software platform, chaos detection principle and methods used for weak signals detection are studied. The model used for simulation is established, then the simulation results of weak periodic signal detection in strong noise atmosphere are given and the steps for detecting weak signals with chaos method are listed. Furthermore, the influence of sampling period on system’s performance is studied. Simulation results show that the chao detection approach proposed in this paper can detect the signal even if it is small to 10-10v, and even when it is in the environment with strong noise, small signal with magnitude of only 5×10-9 v can be found. Chaos method has strong capability for weak signal detection which lay important foundation for exploiting virtual instrument.

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Setoudeh, Farbod, Ali Khaki Sedigh e Mohsen Najafi. "A Novel Method for Chaos Detection in Heavy Noisy Environments Based on Distribution of Energy". International Journal of Bifurcation and Chaos 29, n. 13 (10 dicembre 2019): 1950179. http://dx.doi.org/10.1142/s0218127419501797.

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Detecting chaos in heavy-noise environments is an important issue in many fields of science and engineering. In this paper, first, a new criterion is proposed to recognize chaos from noise based on the distribution of energy. Then, a new method based on stationary wavelet transform (SWT) is presented for chaos detection that is recommended for data that contain more than 60% noise. This method is dependent on the distribution of signal’s energy in different frequency bands based on SWT for chaos detection which is robust to noisy environments. In this method, the effect of white noise and colored noise on the chaotic system is considered. As a case study, the proposed method is applied to detect chaos in two different oscillators based on memristor and memcapacitor. The simulation results are used to display the main points of the paper.

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Wu, Dan Hui, e Xin Wu. "Research on the Influence of Noise to Weak Signal Detection Based on Duffing Equation". Applied Mechanics and Materials 65 (giugno 2011): 5–8. http://dx.doi.org/10.4028/www.scientific.net/amm.65.5.

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Abstract (sommario):

In view of existing questions of misjudgment, low efficiency, and error in detecting weak signal using chaos critical state. The basic form of Duffing equation is firstly established and analyzed in this paper; and then, it describes the principle of weak signal detection based on the change of phase trace; The influence of Noise to weak signal detection performance is researched using chaos critical state detection method; Stochastic resonance phenomenon of the small-signal two-dimensional nonlinear system is found, and that, the research in the paper provides some foundation for enhancing detection signal SNR under the strong noise background and a new way for detecting weal signal using stochastic resonance

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Cheng, Feng Qin, e Yao Wu Shi. "Random Phase Weak Sine Signal Detection Based on Autocorrelation and Chaos Theory". Applied Mechanics and Materials 397-400 (settembre 2013): 2129–33. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.2129.

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Abstract (sommario):

The paper expounds the basic principle of the weak signal detection on chaotic system at first , according to the actual situation that the signal phase is unknown Received in the communication and radar systems, a new chaos detection model is presented based on traditional chaos system, combined with autocorrelation detection technology , completed the random phase weak sinusoidal signal detection. The simulation analysis indicates that the proposed method succeeds in detecting Random Phase weak sinusoidal signal, and furthermore the signal-to-noise threshold is lower than either autocorrelation or chaotic oscillator.

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Manas Kumar Yogi. "Investigating the Scope of Chaos Theory for Cyber Threat Detection". Journal of Trends in Computer Science and Smart Technology 5, n. 3 (settembre 2023): 266–83. http://dx.doi.org/10.36548/jtcsst.2023.3.004.

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Abstract (sommario):

The role of chaos theory in the development of cyber threat detection systems is primarily exploratory and theoretical, with limited practical adoption in recent years. Chaos theory offers interesting concepts that have the potential to enhance cyber threat detection capabilities, but its application in the cybersecurity industry faces challenges and limitations. While chaos theory's practical role in cyber threat detection systems remains limited, its principles have the potential to complement existing methodologies and inspire new approaches to address the complex and dynamic nature of cybersecurity threats. As the field progresses, staying informed about the latest research and developments can help gauge the future scope and impact of chaos theory in cyber threat detection. In this paper, the roles and the principles of chaos theory are investigated and this investigation has indicators representing ample scope of chaos theory in design and development of robust frameworks related to cyber threat detection.

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Haykin, S., e Xiao Bo Li. "Detection of signals in chaos". Proceedings of the IEEE 83, n. 1 (1995): 95–122. http://dx.doi.org/10.1109/5.362751.

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9

Mohammed, Sarah Sabah, e Maher K. Mahmood Al-Azawi. "Performance comparison of some weak signal detection techniques". Indonesian Journal of Electrical Engineering and Computer Science 26, n. 2 (1 maggio 2022): 732. http://dx.doi.org/10.11591/ijeecs.v26.i2.pp732-742.

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Abstract (sommario):

Performance comparison of some weak signal detection techniques is introduced. This comparison is very necessary since different applications require different operating conditions such as signal to noise ratio SNR, bandwidth, coherency, processing time and complexity. Three methods for detecting weak signals are considered. These are based on chaos theory, wavelet transform, and stocastic resonance. A detection algorithm based on a rectangular region in phase space plane is suggested in chaos method. The stocastic resonance method is considered in this research, as it is used for signal detection in underwater at a certain frequency. Simulation results obtained from MATLAB programs verify the studied methods giving an estimation of probability of detection and probability of false alarm versus SNR.

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Chang, Shun-Chang. "Stability, Chaos Detection, and Quenching Chaos in the Swing Equation System". Mathematical Problems in Engineering 2020 (23 dicembre 2020): 1–12. http://dx.doi.org/10.1155/2020/6677084.

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The main objective of this study is to explore the complex nonlinear dynamics and chaos control in power systems. The rich dynamics of power systems were observed over a range of parameter values in the bifurcation diagram. Also, a variety of periodic solutions and nonlinear phenomena could be expressed using various numerical skills, such as time responses, phase portraits, Poincaré maps, and frequency spectra. They have also shown that power systems can undergo a cascade of period-doubling bifurcations prior to the onset of chaos. In this study, the Lyapunov exponent and Lyapunov dimension were employed to identify the onset of chaotic motion. Also, state feedback control and dither signal control were applied to quench the chaotic behavior of power systems. Some simulation results were shown to demonstrate the effectiveness of these proposed control approaches.

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Wu, Zhi-jun, Jin Lei, Di Yao, Ming-hua Wang e Sarhan M. Musa. "Chaos-based detection of LDoS attacks". Journal of Systems and Software 86, n. 1 (gennaio 2013): 211–21. http://dx.doi.org/10.1016/j.jss.2012.07.065.

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Armand Eyebe Fouda, J. S., Bertrand Bodo, Samrat L. Sabat e J. Yves Effa. "A Modified 0-1 Test for Chaos Detection in Oversampled Time Series Observations". International Journal of Bifurcation and Chaos 24, n. 05 (maggio 2014): 1450063. http://dx.doi.org/10.1142/s0218127414500631.

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Abstract (sommario):

The use of binary 0-1 test for chaos detection is limited to detect chaos in oversampled time series observations. In this paper we propose a modified 0-1 test in which, binary 0-1 test is applied to the discrete map of local maxima and minima of the original observable in contrast to the direct observable. The proposed approach successfully detects chaos in oversampled time series data. This is verified by simulating different numerical simulations of Lorenz and Duffing systems. The simulation results show the efficiency and computational gain of the proposed test for chaos detection in the continuous time dynamical systems.

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Wu, Kaixin. "Research on Electronic Signal-Assisted Control System Based on Computer Big Data". Highlights in Science, Engineering and Technology 7 (3 agosto 2022): 232–37. http://dx.doi.org/10.54097/hset.v7i.1064.

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Based on computer big data, this paper proposes a new scheme to realize the detection of weak electronic sinusoidal signals using the sensitivity of chaos to parameters in a specific state. This scheme can effectively detect weak sinusoidal signals deep in the background of color noise. The method of chaos detection is given, and the influence of noise on the system state is analyzed. Simulation experiments show that the chaos detection system is very sensitive to small signals, and has a strong ability to suppress any zero-mean color noise.

14

Falk, H. "Prolog to: Detection of signals in chaos". Proceedings of the IEEE 83, n. 1 (gennaio 1995): 94. http://dx.doi.org/10.1109/jproc.1995.1200273.

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Xu, Hang, Liqiang Li, Ying Li, Jianguo Zhang, Hong Han, Li Liu e Jingxia Li. "Chaos-Based Through-Wall Life-Detection Radar". International Journal of Bifurcation and Chaos 29, n. 07 (30 giugno 2019): 1930020. http://dx.doi.org/10.1142/s0218127419300209.

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We propose a chaos-based through-wall life-detection radar utilizing a wideband Boolean-chaos signal as the radar probe signal. The range between the radar and the human target can be obtained by correlating the chaotic signal reflected from the human target with its delayed duplicate. Actually, this range is modulated periodically by human chest wall displacements along the time axis of recording signal and the modulation frequency is equal to the respiratory frequency. Therefore, we design a life-detection algorithm based on correlation method to extract the human’s respiratory frequency and range information from echo signals. Experimental results demonstrate that our radar can simultaneously detect the respiratory frequency and range of the human target behind a 20-cm-thick wall within the range of at least 5[Formula: see text]m. The dynamic range and range resolution can reach 35[Formula: see text]dB and 15[Formula: see text]cm, respectively. Furthermore, the excellent anti-interference performance of the proposed radar has also been demonstrated, which makes it especially suitable for search and rescue missions in complex electromagnetic environments.

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Schimming, T., e M. Hasler. "Optimal detection of differential chaos shift keying". IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 47, n. 12 (2000): 1712–19. http://dx.doi.org/10.1109/81.899923.

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17

Paffrath, M., e U. Wever. "Adapted polynomial chaos expansion for failure detection". Journal of Computational Physics 226, n. 1 (settembre 2007): 263–81. http://dx.doi.org/10.1016/j.jcp.2007.04.011.

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Hasimoto-Beltrán, Rogelio, e Roxana Ramírez-Ramírez. "Cycle detection for secure chaos-based encryption". Communications in Nonlinear Science and Numerical Simulation 16, n. 8 (agosto 2011): 3203–11. http://dx.doi.org/10.1016/j.cnsns.2010.11.002.

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19

Eyebe Fouda, J. S. Armand, Bertrand Bodo, Guy M. D. Djeufa e Samrat L. Sabat. "Experimental chaos detection in the Duffing oscillator". Communications in Nonlinear Science and Numerical Simulation 33 (aprile 2016): 259–69. http://dx.doi.org/10.1016/j.cnsns.2015.09.011.

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Bhattacharya, J. "Detection of weak chaos in infant respiration". IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 31, n. 4 (2001): 637–42. http://dx.doi.org/10.1109/3477.938266.

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Lloyd, A. L., e D. Lloyd. "Chaos : Its significance and detection in biology". Biological Rhythm Research 26, n. 2 (maggio 1995): 233–52. http://dx.doi.org/10.1080/09291019509360338.

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22

Corron, Ned J., Mark T. Stahl, R. Chase Harrison e Jonathan N. Blakely. "Acoustic detection and ranging using solvable chaos". Chaos: An Interdisciplinary Journal of Nonlinear Science 23, n. 2 (giugno 2013): 023119. http://dx.doi.org/10.1063/1.4808252.

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23

Melosik, M., P. Sniatala e W. Marszalek. "Hardware Trojans detection in chaos-based cryptography". Bulletin of the Polish Academy of Sciences Technical Sciences 65, n. 5 (1 ottobre 2017): 725–32. http://dx.doi.org/10.1515/bpasts-2017-0078.

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Abstract (sommario):

Abstract The paper deals with the security problems in chaotic-based cryptography. In particular, the 0–1 test for chaos is used to detect hardware Trojans in electronic circuits – generators of chaotic bit sequences. The proposed method of detecting hardware Trojans is based on analyzing the original bit sequences through the 0–1 test yielding a simple result, either a number close to 1, when the examined bit sequence is chaotic, or a number close to 0, when the sequence is non-chaotic. A complementary result is a graph of translation variables qc and pc which form a basis of the 0–1 test. The method does not require any extra corrections and can be applied to relatively short sequences of bits. This makes the method quite attractive as the security problems are dealt with at the chaotic generator level, with no need to apply any extractors of randomness. The method is illustrated by numerical examples of simulated Trojans in chaotic bit generators based on the analog Lindberg circuit as well as a discrete system based on the logistic map.

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Carroll, Thomas L. "Chaos for low probability of detection communications". Chaos, Solitons & Fractals 103 (ottobre 2017): 238–45. http://dx.doi.org/10.1016/j.chaos.2017.06.011.

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25

Munch, Stephan B., Tanya L. Rogers, Bethany J. Johnson, Uttam Bhat e Cheng-Han Tsai. "Rethinking the Prevalence and Relevance of Chaos in Ecology". Annual Review of Ecology, Evolution, and Systematics 53, n. 1 (2 novembre 2022): 227–49. http://dx.doi.org/10.1146/annurev-ecolsys-111320-052920.

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Abstract (sommario):

Chaos was proposed in the 1970s as an alternative explanation for apparently noisy fluctuations in population size. Although readily demonstrated in models, the search for chaos in nature proved challenging and led many to conclude that chaos is either rare or nigh impossible to detect. However, in the intervening half-century, it has become clear that ecosystems are replete with the enabling conditions for chaos. Chaos has been repeatedly demonstrated under laboratory conditions and has been found in field data using updated detection methods. Together, these developments indicate that the apparent rarity of chaos was an artifact of data limitations and overreliance on low-dimensional population models. We invite readers to reevaluate the relevance of chaos in ecology, and we suggest that chaos is not as rare or undetectable as previously believed.

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Fenga, Livio. "Time Series Chaos Detection and Assessment via Scale Dependent Lyapunov Exponent". International Journal of Statistics and Probability 5, n. 6 (16 ottobre 2016): 1. http://dx.doi.org/10.5539/ijsp.v5n6p1.

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Many dynamical systems in a wide range of disciplines -- such as engineering, economy and biology -- exhibit complex behaviors generated by nonlinear components which might result in deterministic chaos. While in lab--controlled setups its detection and level estimation is in general a doable task, usually the same does not hold for many practical applications. This is because experimental conditions imply facts like low signal--to--noise ratios, small sample sizes and not--repeatability of the experiment, so that the performances of the tools commonly employed for chaos detection can be seriously affected. To tackle this problem, a combined approach based on wavelet and chaos theory is proposed. This is a procedure designed to provide the analyst with qualitative and quantitative information, hopefully conducive to a better understanding of the dynamical system the time series under investigation is generated from. The chaos detector considered is the well known Lyapunov Exponent. A real life application, using the Italian Electric Market price index, is employed to corroborate the validity of the proposed approach.

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Xiong, Wei, Qingsong Bai, Yuqi Hu, Xing Zhang, Yilu Wu, Guangqiong Xia, Heng Zhou, Jiagui Wu e Zhengmao Wu. "3D parallel pulsed chaos LiDAR system". Optics Express 32, n. 7 (15 marzo 2024): 11763. http://dx.doi.org/10.1364/oe.515059.

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We propose and experimentally demonstrate a parallel pulsed chaos light detection and ranging (LiDAR) system with a high peak power, parallelism, and anti-interference. The system generates chaotic microcombs based on a chip-scale Si3N4 microresonator. After passing through an acousto-optic modulator, the continuous-wave chaotic microcomb can be transformed into a pulsed chaotic microcomb, in which each comb line provides pulsed chaos. Thus, a parallel pulsed chaos signal is generated. Using the parallel pulsed chaos as the transmission signal of LiDAR, we successfully realize a 4-m three-dimensional imaging experiment using a microelectromechanical mirror for laser scanning. The experimental results indicate that the parallel pulsed chaos LiDAR can detect twice as many pixels as direct detection continuous wave parallel chaos LiDAR under a transmission power of -6 dBm, a duty cycle of 25%, and a pulse repetition frequency of 100 kHz. By further increasing the transmission power to 10 dBm, we acquire an 11 cm × 10 cm image of a target scene with a resolution of 30 × 50 pixels. Finally, the anti-jamming ability of the system is evaluated, and the results show that the system can withstand interferences of at least 15 dB.

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Kreidl, T. J. "Chaos in Pulsating Variable Stars: Preliminary Analysis of Photometric Photometry and Observational Constraints of Detection". International Astronomical Union Colloquium 139 (1993): 133. http://dx.doi.org/10.1017/s0252921100117105.

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AbstractChaos theory has been applied to a variety of variable stars, but few convincing candidates for chaos have been identified. Here, well-established analysis methods have been applied to some very extensive data sets of rapidly oscillating Ap (roAp) stars and one white dwarf. It it shown that in spite of the amount of data, the signal-to-noise ratio makes positive detection of chaos extremely difficult, especially due to scintillation noise. A new form of dimension computation is presented and discussed. Simple models were constructed to show what noise levels can be tolerated before the detection of chaos is no longer possible and comparisons are drawn with data that could be obtained in the future from space. The lack of phase and amplitude stability in HD 134214 and mode switching in HD217522 and HD 137949 are pointed out as the possible results of chaos, making frequent monitoring of roAp stars desirable.

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LAU, FRANCIS C. M., e CHI K. TSE. "APPROXIMATE-OPTIMAL DETECTOR FOR CHAOS COMMUNICATION SYSTEMS". International Journal of Bifurcation and Chaos 13, n. 05 (maggio 2003): 1329–35. http://dx.doi.org/10.1142/s0218127403007266.

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Recently, an optimal noncoherent detection technique for chaos-shift-keying digital communication system has been proposed. The computational intensity required, however, increases exponentially with the spreading factor. In this Letter, we propose an approximate-optimal detection technique, whose computational effort increases only linearly with the spreading factor. In particular, we use the chaotic sequences generated by a skew tent map as an example to illustrate the approximate-optimal detection method. The bit error performance of the proposed detector is evaluated by computer simulations and the results are compared with those obtained using the optimal detector.

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Wu, Dan Hui. "Application Research of Chaos Synchronization in Detecting Weak Signal". Advanced Materials Research 271-273 (luglio 2011): 581–85. http://dx.doi.org/10.4028/www.scientific.net/amr.271-273.581.

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The basic form of Duffing equation is firstly analyzed in this paper; and then, it describes the principle of weak signal detection based on the change of phase trace. In view of some key questions existing in weak signal detection based on chaos, a new system is put forward, which detects weak signal utilizing chaotic synchronization characteristics. Utilizing the system, the critical problems of existing in weak signal detection based on chaos can be solved, and that, a imitation experiment validates the project, as a result, the research in the paper provides the foundation of putting chaotic synchronization into practice application to weak signal detection.

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TSE, CHI K., e FRANCIS C. M. LAU. "A RETURN MAP REGRESSION APPROACH FOR NONCOHERENT DETECTION IN CHAOTIC DIGITAL COMMUNICATIONS". International Journal of Bifurcation and Chaos 13, n. 03 (marzo 2003): 685–90. http://dx.doi.org/10.1142/s0218127403006790.

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Abstract (sommario):

Chaos-based communications can be applied advantageously if the property of chaotic systems is suitably exploited. In this Letter a simple noncoherent detection method for chaos-shift-keying (CSK) modulation is proposed, exploiting some distinguishable property of chaotic maps for recovering the digital message. Specifically, the proposed method exploits the difference in the return maps of the signals representing the digital symbols. The determining parameter of the return maps is estimated using a simple regression algorithm. If the parameter strongly characterizes the chaotic map, the detection can achieve very good accuracy. This strong parametric characterization can be achieved by defining the regression model with only one parameter. Using the tent maps as chaos generators, the bit-error-rate under additive white Gaussian noise is studied by computer simulations.

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STEFANSKI, ANDRZEJ, TOMASZ KAPITANIAK e PRZEMYSLAW SZUMINSKI. "USING SYNCHRONIZATION TO DETECT CHAOTIC RESPONSE IN EXTERNALLY FORCED DYNAMICAL SYSTEMS". Fluctuation and Noise Letters 03, n. 02 (giugno 2003): L187—L194. http://dx.doi.org/10.1142/s0219477503001257.

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In this paper we present a simple way of chaos detection in forced dynamical systems. The method exploits a synchronization phenomenon of a set of identical mechanical systems driven by the same external excitation. The properties of this synchronization allow for easy and fast detection of chaos in dynamical systems in a wide range of system parameters. The presented approach can be successfully applied both for discrete-time and continuous-time systems. Some applications of the method are presented.

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Serfaty, Alicia, e N. V. Joshi. "Detection of attractors and chaos in intrinsic photoconductors". Physical Review B 47, n. 7 (15 febbraio 1993): 3983–86. http://dx.doi.org/10.1103/physrevb.47.3983.

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Kanters, J. K., R. J. Cohen, N. H. Holstein-Rathlou e K. H. Chon. "Detection of “Noisy” Chaos in a Time Series". Methods of Information in Medicine 36, n. 04/05 (ottobre 1997): 294–97. http://dx.doi.org/10.1055/s-0038-1636859.

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Abstract:Time series from biological system often displays fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely “noise”. The output from most biological systems is probably the result of both the internal dynamics of the systems, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

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Zhang, Chen, Zhen Bin Gao, Jing Chun Li e Biao Huang. "The Comparison between Chaos Algorithm and Music Algorithm Applied in Weak Signal Detection". Applied Mechanics and Materials 427-429 (settembre 2013): 1552–56. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1552.

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Chaos algorithm is essential in weak signal detection because of its sensibility to weak signals and immunity to noise. This paper applies subspace algorithm which originates from array signal processing to weak signal detection field because of its lower signal to noise ratio. Firstly, the article introduces the principles of two algorithms, then analyses simulation experiments results of real signal data. After that, a conclusion for two algorithms comparison by estimation of computation cost, complexity of implementation and hardware resources occupied is drawn. At the end, the writer designs a duffing chaos module which is the core part of chaotic detection with verilog-hdl.

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Toro-García, Nicolás, Yeison Alberto Garcés-Gómez e Fredy Edimer Hoyos-Velasco. "Voltage Regulation in a Power Inverter Using a Quasi-Sliding Control Technique". DYNA 82, n. 192 (25 agosto 2015): 52–59. http://dx.doi.org/10.15446/dyna.v82n192.48569.

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<p>This paper shows the behavior of a three-phase power converter with resistive load using a quasi-sliding and a chaos control techniques for output voltage regulation. Controller is designed using Zero Average Dynamic (ZAD) and Fixed Point Inducting Control (FPIC) techniques. Designs have been tested in a Rapid Control Prototyping (RCP) system based on Digital Signal Processing (DSP) for dSPACE platform. Bifurcation diagrams show the robustness of the system. Chaos detection is a signal processing method in the time domain, and has power quality phenomena detection applications. Results show that the phase voltage in the load has sinusoidal performance when it is controlled with these techniques. When delay effects are considered, experimental and numerical results match in both of stable and transition to chaos zones.</p>

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Zhang, Ren Cheng, J. H. Yang e Jian Hua Du. "Study on In-Process Detection and Diagnosis of Faults Arc Based on Early Sounds Signature and Intermittent Chaos". Key Engineering Materials 381-382 (giugno 2008): 611–14. http://dx.doi.org/10.4028/www.scientific.net/kem.381-382.611.

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Up to now, faults arc protection in electrical power system is passive by detecting electric current or arcing light. An active technique used to forecast faults arc is presented in this paper. By applying power spectrum density analysis, two signature bands of arc sound has been found before faults arc take place, one is inside of (5~10) kHz which is strong in intensity and variable in both bandwidth and center in different experimental conditions, the other one is situated on 19.25kHz which is weak in intensity but invariable in center. The proposed technique detects the arc sounds signature in the frequency of 19.25 kHz based on Duffing chaos oscillator. The arc sound is recorded using precision fiber microphone and imported into the chaos based detecting system. For the sensitivity to periodic signal, the chaos system appears either pure chaos or intermittent chaos. So arc sound can been identified by detecting the motion state of chaotic system, and the presently fault arc protection method can been improved into an active forecast and early warning one. Some experiment results and fault arc diagnosis and early warning scheme are also detailed in the paper.

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Xu, Hang, Ying Li, Jianguo Zhang, Hong Han, Bing Zhang, Longsheng Wang, Yuncai Wang e Anbang Wang. "Ultra-Wideband Chaos Life-Detection Radar with Sinusoidal Wave Modulation". International Journal of Bifurcation and Chaos 27, n. 13 (15 dicembre 2017): 1730046. http://dx.doi.org/10.1142/s0218127417300464.

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We propose and experimentally demonstrate an ultra-wideband (UWB) chaos life-detection radar. The proposed radar transmits a wideband chaotic-pulse-position modulation (CPPM) signal modulated by a single-tone sinusoidal wave. A narrow-band split ring sensor is used to collect the reflected sinusoidal wave, and a lock-in amplifier is utilized to identify frequencies of respiration and heartbeat by detecting the phase change of the sinusoidal echo signal. Meanwhile, human location is realized by correlating the CPPM echo signal with its delayed duplicate and combining the synthetic aperture technology. Experimental results demonstrate that the human target can be located accurately and his vital signs can be detected in a large dynamic range through a 20-cm-thick wall using our radar system. The down-range resolution is 15[Formula: see text]cm, benefiting from the 1-GHz bandwidth of the CPPM signal. The dynamic range for human location is 50[Formula: see text]dB, and the dynamic ranges for heartbeat and respiration detection respectively are 20[Formula: see text]dB and 60[Formula: see text]dB in our radar system. In addition, the bandwidth of the CPPM signal can be adjusted from 620[Formula: see text]MHz to 1.56[Formula: see text]GHz to adapt to different requirements.

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Kumar, Aniket, Saurabh Kumar Pal, Kumar Dhruv Roy e Mr Ragunthar T. "Fake News Detection". International Journal of Scientific & Engineering Research 11, n. 12 (25 dicembre 2020): 575–80. http://dx.doi.org/10.14299/ijser.2020.12.09.

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Now-a-days it's exceedingly common in this digital world that someone for his or her benefit try to manipulate a mass with false information. With the massive use of social media by the population which is beneficial for the users most of the time, can also be used as a really good platform to spread a fake news and at worse try to create chaos in society. Fake death news of celebrities, fake news regarding wars and fake news related to politics are the day-to-day life examples.

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Zeng, Fang Ling, Yan Yan Hu, Xiao Juan Geng e Shi Gui Zhang. "A New Method of Chaotic Detection for Weak Sinusoidal Signal Frequency". Advanced Materials Research 756-759 (settembre 2013): 265–70. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.265.

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This paper describes the intermittent chaos detection principle, combined with differential form the double Duffing oscillator difference system to the weak signal frequency detection, gives the detailed steps of the method and flow chart. Use the feature that Duffing oscillators with specific reference frequency are insensible to other frequency signals interference, only sensitive to a small part of the nearby specific frequency signal, it comes to a conclusion that small amplitude periodic motion and intermittent chaos motion may appear at the same time in the detection system, which can be used to detect complex frequency signals. At last, takes the single frequency signal and the complex frequency signal detection for simulation, the results show that, compared with traditional Duffing oscillator array method, this method not only reduces the array number, and improved frequency detection bandwidth without affecting the detection accuracy, reduces the calculation amount, so its much better than the traditional method for frequency detection.

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Borrero, Juan D., e Jesus Mariscal. "Deterministic Chaos Detection and Simplicial Local Predictions Applied to Strawberry Production Time Series". Mathematics 9, n. 23 (26 novembre 2021): 3034. http://dx.doi.org/10.3390/math9233034.

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In this work, we attempted to find a non-linear dependency in the time series of strawberry production in Huelva (Spain) using a procedure based on metric tests measuring chaos. This study aims to develop a novel method for yield prediction. To do this, we study the system’s sensitivity to initial conditions (exponential growth of the errors) using the maximal Lyapunov exponent. To check the soundness of its computation on non-stationary and not excessively long time series, we employed the method of over-embedding, apart from repeating the computation with parts of the transformed time series. We determine the existence of deterministic chaos, and we conclude that non-linear techniques from chaos theory are better suited to describe the data than linear techniques such as the ARIMA (autoregressive integrated moving average) or SARIMA (seasonal autoregressive moving average) models. We proceed to predict short-term strawberry production using Lorenz’s Analog Method.

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Liu, Boquan, Evan Polce, Julien C. Sprott e Jack J. Jiang. "Applied Chaos Level Test for Validation of Signal Conditions Underlying Optimal Performance of Voice Classification Methods". Journal of Speech, Language, and Hearing Research 61, n. 5 (17 maggio 2018): 1130–39. http://dx.doi.org/10.1044/2018_jslhr-s-17-0250.

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Purpose The purpose of this study is to introduce a chaos level test to evaluate linear and nonlinear voice type classification method performances under varying signal chaos conditions without subjective impression. Study Design Voice signals were constructed with differing degrees of noise to model signal chaos. Within each noise power, 100 Monte Carlo experiments were applied to analyze the output of jitter, shimmer, correlation dimension, and spectrum convergence ratio. The computational output of the 4 classifiers was then plotted against signal chaos level to investigate the performance of these acoustic analysis methods under varying degrees of signal chaos. Method A diffusive behavior detection–based chaos level test was used to investigate the performances of different voice classification methods. Voice signals were constructed by varying the signal-to-noise ratio to establish differing signal chaos conditions. Results Chaos level increased sigmoidally with increasing noise power. Jitter and shimmer performed optimally when the chaos level was less than or equal to 0.01, whereas correlation dimension was capable of analyzing signals with chaos levels of less than or equal to 0.0179. Spectrum convergence ratio demonstrated proficiency in analyzing voice signals with all chaos levels investigated in this study. Conclusion The results of this study corroborate the performance relationships observed in previous studies and, therefore, demonstrate the validity of the validation test method. The presented chaos level validation test could be broadly utilized to evaluate acoustic analysis methods and establish the most appropriate methodology for objective voice analysis in clinical practice.

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Rajitha, Datla, e Godi Karunakar. "Effect of chaos factor in radiation pattern in planner antenna arrays with chaos adaptive invasive weed optimization". Indonesian Journal of Electrical Engineering and Computer Science 27, n. 2 (1 agosto 2022): 692. http://dx.doi.org/10.11591/ijeecs.v27.i2.pp692-700.

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For mobile <span>communication and spatial detection of antennas should have high directive radiation pattern, in this context pattern synthesis of planar circular antenna arrays is highly significant such design has been done inverse weed optimization. The basic objective e is to study invasive weed optimization in compression with modified chaotic adaptive invasive weed optimization. The focus of the study is the effect of chaotic factors suitable for sinusoidal mapping for chaos as applicable to the context of the design of antennas. Taking various numbers of elements of the antenna and the distance between the antenna’s radiation patterns are studied by varying chaos factors through MATLAB programming. It is found that the critical point of 2.3 for chaos factor makes the map enter into phase of chaos prior to the critical point is a phase of periodicity starting with chaos factor of 2. Below this value there is no chaos but a phase of convergence. These phases are useful having a trade of convergence and chaos. By varying the factor of chaos the impact on the radiation factor of non-uniform planar antennas has been found to give phases of convergence of chaos which are essential for making trade of between exploitation and exploration required in optimization.</span>

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Li, Teng-Hui, Shou-Sheng Xie, Sheng-Ping Liu, Lei Xiao, Wei-Zhou Jia e Da-Wei He. "A fault detection optimization method based on chaos adaptive artificial fish swarm algorithm on distributed control system". Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 232, n. 9 (6 giugno 2018): 1182–93. http://dx.doi.org/10.1177/0959651818777678.

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For the purpose of improving fault detection accuracy of aero-engine distributed control system, an optimal design method based on chaos adaptive artificial fish swarm algorithm for distributed control system fault detection observer was proposed. First, in order to better simulate the actual distributed control system, dual channel multiple packet transmission was converted to switching system and short time-varying delay was modeled as an uncertainty in system models. Then, a fault observer is designed to obtain the state-space model of error system and the chaos adaptive artificial fish swarm algorithm is introduced. Furthermore, the ratio value of the residual signal transfer function, respectively, to the unknown disturbance signal and fault signal, are regarded as the objective function, and the minimum of the objective function is optimized to get the optimal observer matrix by chaos adaptive artificial fish swarm algorithm with the constraint of error system stability. Finally, the structure and operating principle of aero-engine distributed control system semi-physical platform is introduced, and comparison is made between the simulation of fault detection optimization method and the tradition robust fault detection method on the platform. The simulation results verify that the proposed method can efficiently reduce fault positive ratio and fault negative ratio simultaneously, which can expand the selection scope of threshold value and improve accuracy of fault detection.

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Rubežić, Vesna, Igor Djurović e Ervin Sejdić. "Average wavelet coefficient-based detection of chaos in oscillatory circuits". COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 36, n. 1 (3 gennaio 2017): 188–201. http://dx.doi.org/10.1108/compel-05-2016-0198.

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Purpose The purpose of this paper is to propose a new algorithm for detection of chaos in oscillatory circuits. The algorithm is based on the wavelet transform. Design/methodology/approach The proposed detection is developed by using a specific measure obtained by averaging wavelet coefficients. This measure exhibits various values for chaotic and periodic states. Findings The proposed algorithm is applied to signals from autonomous systems such as the Chua’s oscillatory circuit, the Lorenz chaotic system and non-autonomous systems such as the Duffing oscillator. In addition, the detection is applied to sequences obtained from the logistic map. The results are compared to those obtained with a detrended fluctuation analysis and a time-frequency signal analysis based on detectors of chaotic states. Originality/value In this paper, a new algorithm is proposed for the detection of chaos from a single time series. The proposed technique is robust to the noise influence, having smaller calculation complexity with respect to the state-of-the-art techniques. It is suitable for real-time detection with delay that is about half of the window width.

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Gao Shi-Long, Zhong Su-Chuan, Wei Kun e Ma Hong. "Weak signal detection based on chaos and stochastic resonance". Acta Physica Sinica 61, n. 18 (2012): 180501. http://dx.doi.org/10.7498/aps.61.180501.

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HUANG Xin, 黄新, e 刘璋 LIU Zhang. "Lane detection by LDA and chaos particle swarm optimization". Chinese Journal of Liquid Crystals and Displays 32, n. 6 (2017): 491–98. http://dx.doi.org/10.3788/yjyxs20173206.0491.

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Chonka, Ashley, Jaipal Singh e Wanlei Zhou. "Chaos theory based detection against network mimicking DDoS attacks". IEEE Communications Letters 13, n. 9 (settembre 2009): 717–19. http://dx.doi.org/10.1109/lcomm.2009.090615.

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Li, Xiao-Zhou, e Sze-Chun Chan. "Detection Dependencies of Statistical Properties for Semiconductor Laser Chaos". IEEE Journal of Selected Topics in Quantum Electronics 25, n. 6 (novembre 2019): 1–9. http://dx.doi.org/10.1109/jstqe.2019.2914420.

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Tempelman, Joshua R., e Firas A. Khasawneh. "A look into chaos detection through topological data analysis". Physica D: Nonlinear Phenomena 406 (maggio 2020): 132446. http://dx.doi.org/10.1016/j.physd.2020.132446.

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