scholarly journals Identification of Couplings in Adaptive Dynamical Networks of Time-Delayed Feedback Oscillators

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2200
Author(s):  
Ilya V. Sysoev ◽  
Danil D. Kulminskiy ◽  
Vladimir I. Ponomarenko ◽  
Mikhail D. Prokhorov
Keyword(s):  
Time Series ◽  
A Priori ◽  
Linear Optimization ◽  
Target Function ◽  
Delayed Feedback ◽  
Connectivity Matrix ◽  
Nonlinear Functions ◽  
Estimated Parameters ◽  
Unbiased Estimates ◽  
Time Delayed Feedback

An approach to solve the inverse problem of the reconstruction of the network of time-delay oscillators from their time series is proposed and studied in the case of the nonstationary connectivity matrix. Adaptive couplings have not been considered yet for this particular reconstruction problem. The problem of coupling identification is reduced to linear optimization of a specially constructed target function. This function is introduced taking into account the continuity of the nonlinear functions of oscillators and does not exploit the mean squared difference between the model and observed time series. The proposed approach allows us to minimize the number of estimated parameters and gives asymptotically unbiased estimates for a large class of nonlinear functions. The approach efficiency is demonstrated for the network composed of time-delayed feedback oscillators with a random architecture of constant and adaptive couplings in the absence of a priori knowledge about the connectivity structure and its evolution. The proposed technique extends the application area of the considered class of methods.

Reconstruction of time-delayed feedback systems from time series

2005 ◽  
Vol 203 (3-4) ◽  
pp. 209-223 ◽  
Author(s):  
M.D. Prokhorov ◽  
V.I. Ponomarenko ◽  
A.S. Karavaev ◽  
B.P. Bezruchko
Keyword(s):  
Time Series ◽  
Delayed Feedback ◽  
Feedback Systems ◽  
Time Delayed Feedback

scholarly journals Boosting energy-time entanglement using coherent time-delayed feedback

2021 ◽  
Vol 103 (6) ◽  
Author(s):  
Kisa Barkemeyer ◽  
Marcel Hohn ◽  
Stephan Reitzenstein ◽  
Alexander Carmele
Keyword(s):  
Delayed Feedback ◽  
Time Delayed Feedback

scholarly journals Constructing Adaptive Deformation Models for Estimating DEM Error in SBAS-InSAR Based on Hypothesis Testing

2021 ◽  
Vol 13 (10) ◽  
pp. 2006
Author(s):  
Jun Hu ◽  
Qiaoqiao Ge ◽  
Jihong Liu ◽  
Wenyan Yang ◽  
Zhigui Du ◽  
...  
Keyword(s):  
Time Series ◽  
Hypothesis Testing ◽  
Surface Deformation ◽  
A Priori ◽  
Least Square ◽  
Deformation Model ◽  
Phase Time ◽  
Testing Theory ◽  
Sbas Insar ◽  
Deformation Models

The Interferometric Synthetic Aperture Radar (InSAR) technique has been widely used to obtain the ground surface deformation of geohazards (e.g., mining subsidence and landslides). As one of the inherent errors in the interferometric phase, the digital elevation model (DEM) error is usually estimated with the help of an a priori deformation model. However, it is difficult to determine an a priori deformation model that can fit the deformation time series well, leading to possible bias in the estimation of DEM error and the deformation time series. In this paper, we propose a method that can construct an adaptive deformation model, based on a set of predefined functions and the hypothesis testing theory in the framework of the small baseline subset InSAR (SBAS-InSAR) method. Since it is difficult to fit the deformation time series over a long time span by using only one function, the phase time series is first divided into several groups with overlapping regions. In each group, the hypothesis testing theory is employed to adaptively select the optimal deformation model from the predefined functions. The parameters of adaptive deformation models and the DEM error can be modeled with the phase time series and solved by a least square method. Simulations and real data experiments in the Pingchuan mining area, Gaunsu Province, China, demonstrate that, compared to the state-of-the-art deformation modeling strategy (e.g., the linear deformation model and the function group deformation model), the proposed method can significantly improve the accuracy of DEM error estimation and can benefit the estimation of deformation time series.

Effect of time-delayed feedback in a bistable system inferred by logic operation

2021 ◽  
Vol 148 ◽  
pp. 111043
Author(s):  
Rong Gui ◽  
Jiaxin Li ◽  
Yuangen Yao ◽  
Guanghui Cheng
Keyword(s):  
Delayed Feedback ◽  
Bistable System ◽  
Logic Operation ◽  
Time Delayed Feedback

scholarly journals Modeling Noisy Time Series: Physiological Tremor

1998 ◽  
Vol 08 (07) ◽  
pp. 1505-1516 ◽  
Author(s):  
J. Timmer
Keyword(s):  
Time Series ◽  
Stochastic Systems ◽  
State Space Model ◽  
Physiological Tremor ◽  
Space Model ◽  
Deterministic Systems ◽  
Estimated Parameters ◽  
Noisy Time Series ◽  
Observational Noise ◽  
Small Amplitude Oscillation

Empirical time series often contain observational noise. We investigate the effect of this noise on the estimated parameters of models fitted to the data. For data of physiological tremor, i.e. a small amplitude oscillation of the outstretched hand of healthy subjects, we compare the results for a linear model that explicitly includes additional observational noise to one that ignores this noise. We discuss problems and possible solutions for nonlinear deterministic as well as nonlinear stochastic processes. Especially we discuss the state space model applicable for modeling noisy stochastic systems and Bock's algorithm capable for modeling noisy deterministic systems.

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