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Hyperchaos synchronization using PSO-optimized RBF-based controllers to improve security of communication systems
2011
Neural computing & applications (Print)
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These methods use the radial basis function (RBF)based neural controllers for this purpose. The first method uses a standard RBF neural controller. ...
For this method, the coefficients of the error integral component and the parameters of RBF neural network are also derived and optimized via PSO algorithm. ...
Related work Recently, many researchers have studied the control and synchronization of hyperchaotic systems. As examples of studies based on linear control approach, Wang et al. ...
doi:10.1007/s00521-011-0774-4
fatcat:u7dsqqwyrfhorjcxwlyre6mwwi
Nonlinear Analysis of Dynamical Complex Networks 2014
2014
Abstract and Applied Analysis
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Subsequently, in the paper entitled "Timeand event-driven communication process for networked control systems: a survey" by L. ...
For networked control systems (NCSs), especially largescale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities ...
We would like to acknowledge all authors for their efforts in submitting high-quality papers. We are also very grateful to the reviewers for their thorough and on time reviews of the papers. ...
doi:10.1155/2014/976231
fatcat:4pf2zd4h35gazgo2vyhoawgyka
A New RBF Neural Network-Based Fault-Tolerant Active Control for Fractional Time-Delayed Systems
2021
Electronics
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Lastly, by applying the proposed control scheme, synchronization results of the fractional time-delayed memristor system in the presence of faults and uncertainties are studied. ...
Then, a fractional-order memristor system is investigated, and some characteristics of this chaotic system are studied. ...
For 0.98 < q < 0.99, a periodic behavior is observed, and then the system gradually reverts to chaos. Additionally, for (0.84 < q < 0.98) ∪ (0.99 < q < 1) complex behaviors are observed. ...
doi:10.3390/electronics10121501
fatcat:6w6ntgatfrf5jkmo4z3phyh6nq
On-line adaptive chaotic demodulator based on radial-basis-function neural networks
2001
Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
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The demodulator is implemented by an on-line adaptive learning algorithm, which takes advantage of the good approximation capability of the RBF network and the tracking ability of the extended Kalman filter ...
In this paper, an on-line adaptive chaotic demodulator based on a radial-basis-function ͑RBF͒ neural network is proposed and designed. ...
ACKNOWLEDGMENTS This work was supported in part by Hong Kong University Research Grants Council under a competitive-bid earmarked grant, and by Hong Kong Polytechnic University Research Committee. ...
doi:10.1103/physreve.63.026202
pmid:11308553
fatcat:rt7rwd4uzzcvlibkribqlugojq
Nonlinear Dynamics and Entropy of Complex Systems with Hidden and Self-Excited Attractors
2019
Entropy
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In the last few years, entropy has been a fundamental and essential concept in information theory [...] ...
Acknowledgments: We express our thanks to the authors of the above contributions, and to the journal Entropy and MDPI for their support during this work. ...
Conflicts of Interest: The authors declare no conflict of interest. Entropy 2019, 21, 370 ...
doi:10.3390/e21040370
pmid:33267084
pmcid:PMC7514854
fatcat:7jlr56uhanhrhk7en3bbph5knm
A Neural Network Observer-Based Approach for Synchronization of Discrete-Time Chaotic Systems
2008
IFAC Proceedings Volumes
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This paper presents a new approach to solve synchronization problem of a large class of discrete chaotic systems. ...
Then, based on the LPV representation, a neural network observer-based approach is proposed to solve the synchronization problem. ...
Acknowledgments: The authors would like to thanks Iran's Telecommunication Research Centre for their financial support on this research. ...
doi:10.3182/20080706-5-kr-1001.00594
fatcat:y64z35zytfed7iabn74as37qmi
Contents
2021
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)
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…….Zizheng Yan, Guanbin Gao, Jing Na, Fei Liu 372 Iterative Learning Reliable Control for a Kind of Discrete-time Nonlinear Systems with Stochastic Transmission Attenuation and Offset Fault in Actuator ...
State Observer in Rigid-Flexible Coupling Motion Stage ……………………………………………………………..Ruirui Huang, Liyun Su, Yutai Wei, Zhijun Yang 310 Early Warning of Intermittent Failure Based on Hybrid Algorithm ……………… ...
doi:10.1109/ddcls52934.2021.9455485
fatcat:7n7tpgqsuvg55og6dwwuj6g2xe
Table of contents
2020
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)
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for Nonlinear Systems with Prescribed Performance ………………………………….……………………………………………………..…………….Dong Liu 562 A Multi-label Method of State Partition and Fault Diagnosis Based on Binary Relevance Algorithm ...
Xiaohui Li, Jianqiang Shen, Hongfeng Tao, Shoulin Hao 492 A Comparative Study of the First Order Linear ADRC and PI Controller in the Speed Control System of Permanent Magnet Synchronous Motor….……….. ...
Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference November 20-22, 2020, Liuzhou, China ...
doi:10.1109/ddcls49620.2020.9275156
fatcat:kl3b4ptikjhzjn6p7eoqcmwypa
Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions
2021
Applied Sciences
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This paper reviews the recent developments of design optimization methods for electromagnetic devices, with a focus on machine learning methods. ...
Second, a review is presented to the performance prediction and design optimization of electromagnetic devices based on the machine learning algorithms, including artificial neural network, support vector ...
DL is a kind of deep neural network (DNN), and is one subset of machine learning algorithms. ...
doi:10.3390/app11041627
fatcat:jtijw5lngzhcpbqvs47qc5htuq
Hybrid CSA optimization with seasonal RVR in traffic flow forecasting
2017
KSII Transactions on Internet and Information Systems
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Therefore, it is one of the most important components in the research of urban traffic scheduling. ...
Accurate traffic flow forecasting is critical to the development and implementation of city intelligent transportation systems. ...
Traffic flow real-time data can be provided by different kinds of sensor systems that are installed in roads; this data usually includes the flow, speed, and lane occupancy rate of a transportation network ...
doi:10.3837/tiis.2017.10.011
fatcat:ses2ki3pizfgtmyebmqijcoryu
Modeling human cancer-related regulatory modules by GA-RNN hybrid algorithms
2007
BMC Bioinformatics
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This hybrid approach focuses on the construction of various kinds of regulatory modules, that is, Recurrent Neural Network has the capability of controlling feed-forward and feedback loops in regulatory ...
modules and Genetic Algorithms provide the ability of global searching of common regulated genes. ...
Acknowledgements This research work was supported in part by Research Grant NSC95-2221-E-006-321 from the National Science Council, Taiwan. ...
doi:10.1186/1471-2105-8-91
pmid:17359522
pmcid:PMC1838431
fatcat:dchlt7mv5reoxnnx4givfm7dqy
Contents
2011
Procedia Engineering
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. . . . . . . . . . . . . . . . . . . . . . . .. . . . . 969 A Parameterized Design of Reduced-Order State Observer in Linear Control Systems Guo-sheng Wang, Bing Liang and Zeng-xin Tang . . . . . . . ...
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2742 . .
2660
A Papr Reduction Algorithm based on Harmony Research for Ofdm Systems
Jing Gao, Research and Application ...
Monte Carlo Simulation of Energy Distribution of Radiation Field Liu Yi, Chen Xiao-Bai and Wang Chun- Yan . . 3330 An Improved Association Rules Algorithm based on Frequent Item Sets Yaqiong Jiang ...
doi:10.1016/s1877-7058(11)04811-9
fatcat:adrkzzediretxma23pbeqmltvu
Radial basis function neural networks: a topical state-of-the-art survey
2016
Open Computer Science
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They have potential for hybridization and demonstrate some interesting emergent behaviors. This paper aims to offer a compendious and sensible survey on RBF networks. ...
In addition, we have considered the recent research work on optimization of multi-criterions in RBF networks and a range of indicative application areas along with some open source RBFN tools. ...
In recent years, researchers have been focusing on sequential learning algorithms for RBF networks through streams of data. ...
doi:10.1515/comp-2016-0005
fatcat:wm2ik77fi5ca7hbq66ssrnssr4
METHODS FOR QUANTIFYING THE CAUSAL STRUCTURE OF BIVARIATE TIME SERIES
2007
International Journal of Bifurcation and Chaos in Applied Sciences and Engineering
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In the study of complex systems one of the major concerns is the detection and characterization of causal interdependencies and couplings between different subsystems. ...
In this article, we compare a set of six recently introduced methods for quantifying the causal structure of bivariate time series extracted from systems with complex dynamical behavior. ...
direction; (2) C(i) drops sharply at e = 0.7 and remains vanishingly small for e > 0.7 as a result of a transition to a state of synchronization between the two maps. ...
doi:10.1142/s0218127407017628
fatcat:guddg3mwxrhk3n563fot4u4aky
A Survey on Fault Diagnosis and Fault-Tolerant Control Methods for Unmanned Aerial Vehicles
2021
Machines
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In this survey article, we provide a detailed overview of recent advances and studies regarding fault diagnosis, Fault-Tolerant Control (FTC) and anomaly detection for UAVs. ...
The continuous evolution of modern technology has led to the creation of increasingly complex and advanced systems. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/machines9090197
fatcat:53feevbq25ggzdbe4kx3x7kdl4
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