Complex dynamics of a forced discretized version of the Mackey-Glass delay differential equation

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January 2015, 20(1): 93-105. doi: 10.3934/dcdsb.2015.20.93

Complex dynamics of a forced discretized version of the Mackey-Glass delay differential equation

Ahmed Elhassanein ^1,

1.	Math. Dept., Faculty of Science, Damanhour University, Damanhour, Egypt

Received June 2013 Revised April 2014 Published November 2014

Abstract
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In this paper, the chaotic behaviour of a forced discretized version of the Mackey-Glass delay differential equation is considered for different levels of noise intensity. The existence and stability of the equilibria of the skeleton are studied. The modified straight-line stabilization method is used to control chaos. The autocorrelation structure is discussed. Numerical simulations are employed to show the model's complex dynamics by means of the largest Lyapunov exponents, bifurcations, time series diagrams and phase portraits. The effects of noise intensity on its dynamics and the intermittency phenomenon are also discussed via simulation.

Keywords: Physiological systems, noise-induced chaos., chaos, bifurcations, forced Mackey-Glass discrete system.

Mathematics Subject Classification: 37M10, 37N25, 37H10, 37F10, 37G3.

Citation: Ahmed Elhassanein. Complex dynamics of a forced discretized version of the Mackey-Glass delay differential equation. Discrete and Continuous Dynamical Systems - B, 2015, 20 (1) : 93-105. doi: 10.3934/dcdsb.2015.20.93

References:

[1]	I. Bashkirtseva and L. Ryashko, Stochastic sensitivity analysis of noise-induced intermittency and transition to chaos in one-dimensional discrete-time systems, Physica A, 392 (2013), 295-306. doi: 10.1016/j.physa.2012.09.001.
[2]	J. Brockwell and A. Davis, Time Series: Theory and Methods, $2^{nd}$ edition, Springer-Verlag, New York, 2006. doi: 10.1007/978-1-4419-0320-4.
[3]	J. H. E. Cartwright, Nonlinear stiffness, Lyapunov exponents, and attractor dimension, Phys. Lett. A, 264 (1999), 298-302. doi: 10.1016/S0375-9601(99)00793-8.
[4]	S. Chatterjee and M. Yilmaz, Chaos, fractals and statistics, Statist. Sci., 7 (1992), 49-68. Available from: http://www.jstor.org/discover/10.2307/2245990?uid=2&uid=4&sid=21104445119883. doi: 10.1214/ss/1177011443.
[5]	R. L. Devaney, An Introduction to Chaotic Dynamical Systems, Addison-Wesely Reading, 1989.
[6]	J. Du, T. Huang and Z. Sheng, Analysis of decision-making in economic chaos control, Nonlinear Anal. Real World Appl., 10 (2009), 2493-2501. doi: 10.1016/j.nonrwa.2008.05.007.
[7]	S. N. Elaydi, An Introduction to Difference Equations, $3^{rd}$ edition, Springer-Verlag, New York, 2005.
[8]	A. Elhassanein, Complex dynamics of logistic self-exciting threshold autoregressive model, J. Comput. Theor. Nanosci., accepted.
[9]	A. Elhassanein, On the control of forced process feedback nonlinear autoregressive model, J. Comput. Theor. Nanosci., accepted.
[10]	A. Elhassanein, Complex dynamics of a stochastic discrete modified Leslie-Gower predator-prey model with Michaelis-Menten type prey harvesting, Computational Ecology and Software, 4 (2014), 116-128. Available from: http://www.iaees.org/publications/journals/ces/articles/2014-4(2)/dynamics-of-a-stochastic-discrete-modified-Leslie-Gower-model.pdf.
[11]	A. Elhassanein, On the theory of continuous time series, Indian J. Pure Appl. Math., 45 (2014), 297-310. doi: 10.1007/s13226-014-0064-9.
[12]	A. Elhassanein, Nonparametric spectral analysis on disjoint segments of observations, JAMSI, 7 (2011), 81-96. Available from: http://jamsi.fpv.ucm.sk/docs/v07n01_05_2011/v07_n01_07_ELHASSANEIN.pdf.
[13]	W. A. Fuller, Introduction to Statistical Time Series, John Wiley & Sones, 1996.
[14]	J. Gao, J. Hu, W. Tung and Y. Zheng, Multiscale analysis of economic time series by scale-dependent Lyapunov exponent, Quantitative Finance, 13 (2013), 265-274. doi: 10.1080/14697688.2011.580774.
[15]	M. A. Ghazal and A. Elhassanein, Dynamics of EXPAR models for high frequency data, Int. J. Appl. Math. Stat., 14 (2009), 88-96. Available from: http://www.ceser.in/ceserp/index.php/ijamas/article/view/165.
[16]	M. A. Ghazal and A. Elhassanein, Spectral analysis of time series in joint segments of observations, J. Appl. Math. & Informatics, 26 (2008), 933-943. Available from: http://www.kcam.biz/contents/table_contents_view.php?Len=&idx=818.
[17]	M. A. Ghazal and A. Elhassanein, Nonparametric spectral analysis of continuous time Series, Bull. Stat. Econ., 1 (2007), 41-52. Available from: http://www.ceserp.com/cp-jour/index.php?journal=bse&page=article&op=view&path[]=483.
[18]	M. A. Ghazal and A. Elhassanein, Periodogram analysis with missing observations, J. Appl. Math. Comput., 22 (2006), 209-222. doi: 10.1007/BF02896472.
[19]	D. Gulick, Encounters with Chaos, McGraw Hill, New York, 1992.
[20]	L. Junges and J. A. C. Gallas, Intricate routes to chaos in the Mackey-Glass delayed feed back system, Physics letters A, 376 (2012), 2109-2116. doi: 10.1016/j.physleta.2012.05.022.
[21]	J. L. Kaplan and Y. A. Yorke, A regime observed in a fluid flow model of Lorenz, Comm. Math. Phys., 67 (1979), 93-108. Available from: http://projecteuclid.org/euclid.cmp/1103905158. doi: 10.1007/BF01221359.
[22]	M. Karanasos and C. Kyrtsou, Analyzing the link between stock volatility and volume by a Mackey-Glass GARCH-type model: The case of Korea, Quantitative and Qualitative Analysis in Social Sciences, 5 (2011), 49-69. Available from: http://www.qass.org.uk/2011/paper4.pdf.
[23]	C. Kyrtsou and M. Terraza, Seasonal Mackey-Glass-GARCH process and short-term dynamics, Emp. Econ., 38 (2010), 325-345. doi: 10.1007/s00181-009-0268-8.
[24]	C. Kyrtsou, Re-examining the sources of heteroskedasticity: The paradigm of noisy chaotic models, Physica A, 387 (2008), 6785-6789. doi: 10.1016/j.physa.2008.09.008.
[25]	C. Kyrtsou, Evidence for neglected linearity in noisy chaotic models, Int. J. Bifurcation Chaos, 15 (2005), 3391-3394. doi: 10.1142/S0218127405013964.
[26]	C. Kyrtsou, W. Labys and M. Terraza, Terraza, Noisy chaotic dynamics in commodity markets, Emp. Econ., 29 (2004), 489-502. doi: 10.1007/s00181-003-0180-6.
[27]	C. Kyrtsou and M. Terraza, Is it possible to study chaotic and ARCH behaviour jointly? Application of a noisy Mackey-Glass equation with heteroskedastic errors to the Paris stock exchange returns series, Computational Economics, 21 (2003), 257-276. doi: 10.1023/A:1023939610962.
[28]	P. S. Landa and M. G. Rosenblum, Modefied Mackey-Glass model of respiration control, Physical Review E, 52 (1995), 36-39. doi: 10.1103/PhysRevE.52.R36.
[29]	J. Losson, M. C. Mackey and A. Longtin, Solution multistability in first order nonlinear differential delay equations, Chaos, 3 (1993), 167-176. doi: 10.1063/1.165982.
[30]	M. C. Mackey, M. Santill'an and N. Yildirim, Modeling operon dynamics: The trytophan and lactose operation as paradigms, C. R. Biologies, 327 (2004), 211-224. doi: 10.1016/j.crvi.2003.11.009.
[31]	M. C. Mackey and L. Glass, Oscillation and chaos in physiological control system, Science, 197 (1977), 287-289.
[32]	A. E. Matouk and H. N. Agiza, Bifurcations, chaos and synchronization in ADVP circuit with parallel resistor, J. Math. Anal. Appl., 341 (2008), 259-269. doi: 10.1016/j.jmaa.2007.09.067.
[33]	A. Matsumoto, Controlling the Cournot-Nash chaos, J. Optim. Theory Appl., 128 (2006), 379-392. doi: 10.1007/s10957-006-9021-z.
[34]	R. K. Miller and A. N. Michael, Ordinary Differential Equations, Academic Press, New York, 1982.
[35]	I. Ncube, Stability switching and Hopf bifurcation in a multiple-delayed neural network with distributed delay, J. Math. Anal. Appl., 407 (2013), 141-146. doi: 10.1016/j.jmaa.2013.05.021.
[36]	D. T. Nguyen, Mackey-Glass equation driven by fractional Brownian motion, Physica A, 391 (2012), 5465-5472. doi: 10.1016/j.physa.2012.06.013.
[37]	B. Niu and W. Jiang, Nonresonant Hopf-Hopf bifurcation and a chaotic attractor in neutral functional differential equations, J. Math. Anal. Appl., 398 (2013), 362-371. doi: 10.1016/j.jmaa.2012.08.051.
[38]	G. Qi, Z. Chen and Z. Yuan, Adaptive high order differential feedback control for affine nonlinear system, Chaos, Solitons & Fractals, 37 (2008), 308-315. doi: 10.1016/j.chaos.2006.09.027.
[39]	H. Xu, G. Wang and S. Chen, Controlling chaos by a modified straight-line stabilization method, The European Physical Journal B, 22 (2001), 65-69. doi: 10.1007/PL00011136.

show all references

References:

[1]	I. Bashkirtseva and L. Ryashko, Stochastic sensitivity analysis of noise-induced intermittency and transition to chaos in one-dimensional discrete-time systems, Physica A, 392 (2013), 295-306. doi: 10.1016/j.physa.2012.09.001.
[2]	J. Brockwell and A. Davis, Time Series: Theory and Methods, $2^{nd}$ edition, Springer-Verlag, New York, 2006. doi: 10.1007/978-1-4419-0320-4.
[3]	J. H. E. Cartwright, Nonlinear stiffness, Lyapunov exponents, and attractor dimension, Phys. Lett. A, 264 (1999), 298-302. doi: 10.1016/S0375-9601(99)00793-8.
[4]	S. Chatterjee and M. Yilmaz, Chaos, fractals and statistics, Statist. Sci., 7 (1992), 49-68. Available from: http://www.jstor.org/discover/10.2307/2245990?uid=2&uid=4&sid=21104445119883. doi: 10.1214/ss/1177011443.
[5]	R. L. Devaney, An Introduction to Chaotic Dynamical Systems, Addison-Wesely Reading, 1989.
[6]	J. Du, T. Huang and Z. Sheng, Analysis of decision-making in economic chaos control, Nonlinear Anal. Real World Appl., 10 (2009), 2493-2501. doi: 10.1016/j.nonrwa.2008.05.007.
[7]	S. N. Elaydi, An Introduction to Difference Equations, $3^{rd}$ edition, Springer-Verlag, New York, 2005.
[8]	A. Elhassanein, Complex dynamics of logistic self-exciting threshold autoregressive model, J. Comput. Theor. Nanosci., accepted.
[9]	A. Elhassanein, On the control of forced process feedback nonlinear autoregressive model, J. Comput. Theor. Nanosci., accepted.
[10]	A. Elhassanein, Complex dynamics of a stochastic discrete modified Leslie-Gower predator-prey model with Michaelis-Menten type prey harvesting, Computational Ecology and Software, 4 (2014), 116-128. Available from: http://www.iaees.org/publications/journals/ces/articles/2014-4(2)/dynamics-of-a-stochastic-discrete-modified-Leslie-Gower-model.pdf.
[11]	A. Elhassanein, On the theory of continuous time series, Indian J. Pure Appl. Math., 45 (2014), 297-310. doi: 10.1007/s13226-014-0064-9.
[12]	A. Elhassanein, Nonparametric spectral analysis on disjoint segments of observations, JAMSI, 7 (2011), 81-96. Available from: http://jamsi.fpv.ucm.sk/docs/v07n01_05_2011/v07_n01_07_ELHASSANEIN.pdf.
[13]	W. A. Fuller, Introduction to Statistical Time Series, John Wiley & Sones, 1996.
[14]	J. Gao, J. Hu, W. Tung and Y. Zheng, Multiscale analysis of economic time series by scale-dependent Lyapunov exponent, Quantitative Finance, 13 (2013), 265-274. doi: 10.1080/14697688.2011.580774.
[15]	M. A. Ghazal and A. Elhassanein, Dynamics of EXPAR models for high frequency data, Int. J. Appl. Math. Stat., 14 (2009), 88-96. Available from: http://www.ceser.in/ceserp/index.php/ijamas/article/view/165.
[16]	M. A. Ghazal and A. Elhassanein, Spectral analysis of time series in joint segments of observations, J. Appl. Math. & Informatics, 26 (2008), 933-943. Available from: http://www.kcam.biz/contents/table_contents_view.php?Len=&idx=818.
[17]	M. A. Ghazal and A. Elhassanein, Nonparametric spectral analysis of continuous time Series, Bull. Stat. Econ., 1 (2007), 41-52. Available from: http://www.ceserp.com/cp-jour/index.php?journal=bse&page=article&op=view&path[]=483.
[18]	M. A. Ghazal and A. Elhassanein, Periodogram analysis with missing observations, J. Appl. Math. Comput., 22 (2006), 209-222. doi: 10.1007/BF02896472.
[19]	D. Gulick, Encounters with Chaos, McGraw Hill, New York, 1992.
[20]	L. Junges and J. A. C. Gallas, Intricate routes to chaos in the Mackey-Glass delayed feed back system, Physics letters A, 376 (2012), 2109-2116. doi: 10.1016/j.physleta.2012.05.022.
[21]	J. L. Kaplan and Y. A. Yorke, A regime observed in a fluid flow model of Lorenz, Comm. Math. Phys., 67 (1979), 93-108. Available from: http://projecteuclid.org/euclid.cmp/1103905158. doi: 10.1007/BF01221359.
[22]	M. Karanasos and C. Kyrtsou, Analyzing the link between stock volatility and volume by a Mackey-Glass GARCH-type model: The case of Korea, Quantitative and Qualitative Analysis in Social Sciences, 5 (2011), 49-69. Available from: http://www.qass.org.uk/2011/paper4.pdf.
[23]	C. Kyrtsou and M. Terraza, Seasonal Mackey-Glass-GARCH process and short-term dynamics, Emp. Econ., 38 (2010), 325-345. doi: 10.1007/s00181-009-0268-8.
[24]	C. Kyrtsou, Re-examining the sources of heteroskedasticity: The paradigm of noisy chaotic models, Physica A, 387 (2008), 6785-6789. doi: 10.1016/j.physa.2008.09.008.
[25]	C. Kyrtsou, Evidence for neglected linearity in noisy chaotic models, Int. J. Bifurcation Chaos, 15 (2005), 3391-3394. doi: 10.1142/S0218127405013964.
[26]	C. Kyrtsou, W. Labys and M. Terraza, Terraza, Noisy chaotic dynamics in commodity markets, Emp. Econ., 29 (2004), 489-502. doi: 10.1007/s00181-003-0180-6.
[27]	C. Kyrtsou and M. Terraza, Is it possible to study chaotic and ARCH behaviour jointly? Application of a noisy Mackey-Glass equation with heteroskedastic errors to the Paris stock exchange returns series, Computational Economics, 21 (2003), 257-276. doi: 10.1023/A:1023939610962.
[28]	P. S. Landa and M. G. Rosenblum, Modefied Mackey-Glass model of respiration control, Physical Review E, 52 (1995), 36-39. doi: 10.1103/PhysRevE.52.R36.
[29]	J. Losson, M. C. Mackey and A. Longtin, Solution multistability in first order nonlinear differential delay equations, Chaos, 3 (1993), 167-176. doi: 10.1063/1.165982.
[30]	M. C. Mackey, M. Santill'an and N. Yildirim, Modeling operon dynamics: The trytophan and lactose operation as paradigms, C. R. Biologies, 327 (2004), 211-224. doi: 10.1016/j.crvi.2003.11.009.
[31]	M. C. Mackey and L. Glass, Oscillation and chaos in physiological control system, Science, 197 (1977), 287-289.
[32]	A. E. Matouk and H. N. Agiza, Bifurcations, chaos and synchronization in ADVP circuit with parallel resistor, J. Math. Anal. Appl., 341 (2008), 259-269. doi: 10.1016/j.jmaa.2007.09.067.
[33]	A. Matsumoto, Controlling the Cournot-Nash chaos, J. Optim. Theory Appl., 128 (2006), 379-392. doi: 10.1007/s10957-006-9021-z.
[34]	R. K. Miller and A. N. Michael, Ordinary Differential Equations, Academic Press, New York, 1982.
[35]	I. Ncube, Stability switching and Hopf bifurcation in a multiple-delayed neural network with distributed delay, J. Math. Anal. Appl., 407 (2013), 141-146. doi: 10.1016/j.jmaa.2013.05.021.
[36]	D. T. Nguyen, Mackey-Glass equation driven by fractional Brownian motion, Physica A, 391 (2012), 5465-5472. doi: 10.1016/j.physa.2012.06.013.
[37]	B. Niu and W. Jiang, Nonresonant Hopf-Hopf bifurcation and a chaotic attractor in neutral functional differential equations, J. Math. Anal. Appl., 398 (2013), 362-371. doi: 10.1016/j.jmaa.2012.08.051.
[38]	G. Qi, Z. Chen and Z. Yuan, Adaptive high order differential feedback control for affine nonlinear system, Chaos, Solitons & Fractals, 37 (2008), 308-315. doi: 10.1016/j.chaos.2006.09.027.
[39]	H. Xu, G. Wang and S. Chen, Controlling chaos by a modified straight-line stabilization method, The European Physical Journal B, 22 (2001), 65-69. doi: 10.1007/PL00011136.

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