Control reconstruction under changes of part of the coordinates of a nonlinear delay dynamical system

2010 ◽  
Vol 46 (8) ◽  
pp. 1188-1201 ◽  
Author(s):  
N. A. Kuz’mina ◽  
V. I. Maksimov
Keyword(s):  
Dynamical System ◽  
Delay Dynamical System ◽  
Nonlinear Delay

TWO-SCROLL ATTRACTOR IN A DELAY DYNAMICAL SYSTEM

2007 ◽  
Vol 17 (10) ◽  
pp. 3455-3460 ◽  
Author(s):  
ARŪNAS TAMAŠEVIČIUS ◽  
TATJANA PYRAGIENĖ ◽  
MANTAS MEŠKAUSKAS
Keyword(s):  
Dynamical System ◽  
Time Delay ◽  
Nonlinear Function ◽  
Delay System ◽  
The Novel ◽  
Type Function ◽  
Delay Dynamical System ◽  
Glass Type ◽  
Electronic Oscillator

Nonvanishing 𐑍-shaped nonlinear function has been introduced in delay dynamical system instead of commonly used Mackey–Glass type function. Depending on time delay the system exhibits not only mono-scroll, but also more complex two-scroll hyperchaotic attractors. Delay system with the novel nonlinear function can be implemented as an analogue electronic oscillator.

scholarly journals New stability results of the delay dynamical system via a novel relaxed condition

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Xiao Cai ◽  
Oh Min Kwon ◽  
Kaibo Shi ◽  
Kun She ◽  
Kun She ◽  
...  
Keyword(s):  
Dynamical System ◽  
Delay Dynamical System ◽  
Stability Results

STABILITY ANALYSIS OF A DISCRETE NONLINEAR DELAY SURVIVAL RED BLOOD CELLS MODEL

2012 ◽  
Vol 05 (04) ◽  
pp. 1250030
Author(s):  
SHUFANG MA ◽  
YUANGANG ZU
Keyword(s):  
Dynamical System ◽  
Stability Analysis ◽  
Red Blood Cells ◽  
Blood Cells ◽  
Discrete Dynamical System ◽  
Original System ◽  
Discrete Delay ◽  
The Stability ◽  
Stability Results ◽  
Nonlinear Delay

In this article we consider the kth-order discrete delay survival red blood cells model. The general form of the discrete dynamical system is rewritten as xn+1 = f(Pn, δn, xn, …, xn+1) where Pn, δn converge to the parametric values P and δ. We show that when the parameters are replaced by sequences, the stability results of the original system still hold.

Parameter estimation of a delay dynamical system using synchronization in presence of noise

2007 ◽  
Vol 32 (4) ◽  
pp. 1278-1284 ◽  
Author(s):  
Biswambhar Rakshit ◽  
A. Roy Chowdhury ◽  
Papri Saha
Keyword(s):  
Dynamical System ◽  
Parameter Estimation ◽  
Delay Dynamical System

scholarly journals The reproductive number R0 of COVID-19 based on estimate of a statistical time delay dynamical system

2020 ◽  
Author(s):  
Nian Shao ◽  
Jin Cheng ◽  
Wenbin Chen
Keyword(s):  
Dynamical System ◽  
Growth Rate ◽  
Time Delay ◽  
Dynamic System ◽  
Reproductive Number ◽  
Generation Interval ◽  
Delay Dynamical System ◽  
Simulation Results ◽  
Statistical Time

AbstractIn this paper, we estimate the reproductive number R0 of COVID-19 based on Wallinga and Lipsitch framework [11] and a novel statistical time delay dynamic system. We use the observed data reported in CCDC’s paper to estimate distribution of the generation interval of the infection and apply the simulation results from the time delay dynamic system as well as released data from CCDC to fit the growth rate. The conclusion is: Based our Fudan-CCDC model, the growth rate r of COVID-19 is almost in [0.30, 0.32] which is larger than the growth rate 0.1 estimated by CCDC [9], and the reproductive number R0 of COVID-19 is estimated by 3.25 ≤ R0 ≤ 3.4 if we simply use R = 1 + r ∗ Tc with Tc = 7.5, which is bigger than that of SARS. Some evolutions and predictions are listed.

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