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Existence of chaos for a simple delay difference equation
Advances in Difference Equations volumeÂ 2015, ArticleÂ number:Â 39 (2015)
Abstract
In this paper, we study the existence of chaos for a simple delay difference equation. By using the snapback repeller theory, we prove that the system is chaotic in the sense of both Devaney and LiYorke when the parameters of this system satisfy some mild conditions. For illustrating the theoretical result, we give two computer simulations.
1 Introduction
Time delay appears in many realistic systems with feedback in science and engineering. It affects the behaviors of a dynamical system significantly. The main reason is that it causes a system to be infinite dimensional. For example, UÃ§ar [1] proposed and analyzed a very simple firstorder delay differential equation that would admit decaying, oscillatory, and even chaotic solutions. Recently, many researchers studied the following delay differential equation:
where a, b are real parameters, \(\tau >0\) is the delay, and \(f:{\mathbf{R}}\to{\mathbf{R}}\) is a real function. Equation (1) is known as a generalization of a neural network. When the function \(f(x)\) is taken as \(\tanh(x)\), (1) becomes a neural network, which was studied in [2] for the stability characteristics. Particularly, in [3â€“5], the authors studied the stability and chaos when \(f(x)\) and the system parameters a, b satisfy some specific conditions.
It is well known that we can use the discrete analog to study the complex dynamical behaviors of nonlinear differential systems. Some qualitative properties of the corresponding difference equations can provide much useful information for analyzing the properties of the original differential equations. Therefore, it is very important to study properties of difference equations. Many researchers had studied the following delay difference equation:
where c is a parameter, k is a positive integer, and \(g:{\mathbf{R}}\to{\mathbf{R}}\) is a map. Equation (2) can be viewed as the Euler discretization of (1) for \(b=1\). Such an equation arises from some of the earliest mathematical models of the macroeconomic â€˜trade cycleâ€™, and has attracted a great deal of attention; see [6â€“11], and many references therein. Most of them studied the permanence, boundedness, stability, attractivity, oscillations, and bifurcations.
For the research on chaotic behavior of (2) or discretization of (1), even for some special forms of them, there are few results which are studied with rigorously mathematical proofs. To the best of our knowledge, most of the existing results are studied with the aid of computer simulations. The main goal of this paper is to study the existence of chaos in the discrete analog of (1). However, it is very difficult to study chaos for a general function f. In [12], Sprott proposed a simple prototype model with a sinusoidal nonlinearity to study chaos for delay differential equations, which is regarded as one of the simplest chaotic delay differential equations. This motivates us to use the sine function as an example to explore the chaotic behavior in discrete analog of (1). That is, we study the existence of chaos of the following delay difference equation:
where Î±, Î², Î³ are real parameters, and k is a positive integer.
This paper is organized as follows. In Section 2, we give some basic concepts and one lemma. In Section 3, we prove that the delay difference equation is chaotic in the sense of both Devaney and LiYorke under some conditions, by using the snapback repeller theory. Then we give two computer simulations to illustrate the theoretical result. Finally, we conclude this paper in Section 4.
2 Preliminaries
Up to now, there is no unified definition of chaos in mathematics. For convenience, we list two definitions of chaos which will be used in this paper.
Definition 1
[13]
Let \((X,d)\) be a metric space, \(F:X\to X\) be a map, and S be a set of X with at least two distinct points. Then S is called a scrambled set of F if for any two distinct points \(x,y\in S\),

(i)
\(\liminf_{n\to\infty}d(F^{n}(x),F^{n}(y))=0\);

(ii)
\(\limsup_{n\to\infty}d(F^{n}(x),F^{n}(y))>0\).
The map F is said to be chaotic in the sense of LiYorke if there exists an uncountable scrambled set S of F.
Remark 1
The term â€˜chaosâ€™ was first used by Li and Yorke [14] for a map on a compact interval. Following the work of Li and Yorke, Zhou [13] gave the above definition of chaos for a topological dynamical system on a general metric space.
Definition 2
[15]
Let \((X,d)\) be a metric space. A map \(F:V\subset X\to V\) is said to be chaotic on V in the sense of Devaney if

(i)
the set of the periodic points of F is dense in V;

(ii)
F is topologically transitive in V;

(iii)
F has sensitive dependence on initial conditions in V.
Remark 2
If F is continuous in V, then condition (iii) can be concluded by conditions (i) and (ii), which was shown by Banks et al. [16]. Consequently, condition (iii) is unnecessary in Definition 2 if F is continuous in V. In [17], Huang and Ye showed that chaos in the sense of Devaney is stronger than that in the sense of LiYorke under some conditions.
In the rest of the paper, we use \(B_{r}(z)\) and \(\bar{B}_{r}(z)\) to denote the open and closed balls of radius r centered at \(z\in X\), respectively. The following definitions in [18] are used in this paper.
Definition 3
[18, Definitions 2.12.4]
Let \((X,d)\) be a metric space and \(F:X\to X\) be a map.

(i)
A point \(z\in X\) is called an expanding fixed point (or a repeller) of F in \(\bar{B}_{r}(z)\) for some constant \(r>0\), if \(F(z)=z\) and there exists a constant \(\lambda>1\) such that
$$d\bigl(F(x),F(y)\bigr)\geq\lambda\,d(x,y) \quad \forall x, y\in\bar{B}_{r}(z). $$The constant Î» is called an expanding coefficient of F in \(\bar{B}_{r}(z)\). Furthermore, z is called a regular expanding fixed point of F in \(\bar{B}_{r}(z)\) if z is an interior point of \(F(B_{r}(z))\). Otherwise, z is called a singular expanding fixed point of F in \(\bar{B}_{r}(z)\).

(ii)
Assume that z is an expanding fixed point of F in \(\bar{B}_{r}(z)\) for some \(r>0\). Then z is said to be a snapback repeller of F if there exists a point \(x_{0}\in B_{r}(z)\) with \(x_{0}\neq z\) and \(F^{m}(x_{0})=z\) for some positive integer m. Furthermore, z is said to be a nondegenerate snapback repeller of F if there exist positive constants Î¼ and \(r_{0}< r\) such that \(B_{r_{0}}(x_{0})\subset B_{r}(z)\) and
$$d\bigl(F^{m}(x),F^{m}(y)\bigr)\geq \mu \, d(x,y) \quad \forall x,y\in B_{r_{0}}(x_{0}). $$z is called a regular snapback repeller of F if \(F(B_{r}(z))\) is open and there exists a positive constant \(\delta_{0}\) such that \(B_{\delta_{0}}(x_{0})\subset B_{r}(z)\) and for each positive constant \(\delta\leq \delta_{0}\), z is an interior point of \(F^{m}(B_{\delta}(x_{0}))\). Otherwise, z is called a singular snapback repeller of F.
Remark 3
The concept of snapback repeller for maps in \({\mathbf{R}}^{n}\) was introduced by Marotto [19] in 1978. Obviously, Definition 3 is given in general metric spaces, which is an extension of Marottoâ€™s definition. In terms of Definition 3, the snapback repeller given by Marotto [19] is regular and nondegenerate.
Lemma 1
([20, Theorem 4.4], [21, Theorem 2.1])
Let \(F:{\mathbf{R}}^{n}\to{\mathbf{R}}^{n}\) be a map with a fixed point \(z\in{\mathbf{R}}^{n}\). Assume that

(i)
F is continuously differentiable in a neighborhood of z and all the eigenvalues of \(\operatorname {DF}(z)\) have absolute values larger than 1, which implies that there exist a positive constant r and a norm \(\Vert \cdot \Vert \) in \({\mathbf{R}}^{n}\) such that F is expanding in \(\bar{B}_{r}(z)\) in \(\Vert \cdot \Vert \);

(ii)
z is a snapback repeller of F with \(F^{m}(x_{0})=z\), \(x_{0}\neq z\), for some \(x_{0}\in B_{r}(z)\) and some positive integer m. Furthermore, F is continuously differentiable in some neighborhoods of \(x_{0},x_{1},\ldots,x_{m1}\), respectively, and \(\det \operatorname {DF}(x_{j})\neq0\) for \(0\leq j\leq m1\), where \(x_{j}=F(x_{j1})\) for \(1\leq j\leq m1\).
Then for each neighborhood U of z, there exist a positive integer \(k>m\) and a Cantor set \(\Lambda\subset U\) such that \(F^{k}:\Lambda\to\Lambda\) is topologically conjugate to the symbolic dynamical system \(\sigma :\sum_{2}^{+}\to\sum_{2}^{+}\). Consequently, there exists a compact and perfect invariant set \(V\subset{\mathbf{R}}^{n}\), containing the Cantor set Î›, such that F is chaotic on V in the sense of Devaney as well as in the sense of LiYorke, and has a dense orbit in V.
Remark 4
We can easily conclude that z is a regular and nondegenerate snapback repeller from Lemma 1. Hence, Lemma 1 can be summed as a single word: â€˜a regular and nondegenerate snapback repeller in \({\mathbf{R}}^{n}\) implies chaos in the sense of both Devaney and LiYorkeâ€™. For more details, one can see [20, 21].
3 Existence of chaos
Let \(u_{j}(n):=x(n+jk1)\) for \(1\leq j\leq k+1\), then (3) is changed into a \((k+1)\)dimensional system on \({\mathbf{R}}^{k+1}\),
where \(u=(u_{1},u_{2},\ldots,u_{k+1})^{T}\in{\mathbf{R}}^{k+1}\).
System (4) is called the system induced by (3) in \({\mathbf{R}}^{k+1}\). It is clear that a solution \(\{x(nk),\ldots,x(n)\}_{n=1}^{\infty}\) of (3) corresponds to a solution \(\{u(n)\}_{n=1}^{\infty}\) of system (4), where the initial condition \(\{x(k),\ldots,x(0)\}\) of (3) corresponds to an initial condition \(u(0)=(u_{1}(0),\ldots,u_{k+1}(0))^{T}\in{\mathbf{R}}^{k+1}\) of system (4). Hence, we can study the dynamical behavior of (3) by studying that of its induced system (4) in \({\mathbf{R}}^{k+1}\). So, we call (3) is chaotic in the sense of Devaney (or LiYorke) on \(V\subset{\mathbf{R}}^{k+1}\) if its induced system (4) is chaotic in the sense of Devaney (or LiYorke) on \(V\subset {\mathbf{R}}^{k+1}\).
Now, we state the main result of this paper as the following theorem.
Theorem 1
There exists a constant \(\beta _{0}>0\) such that for arbitrary Î² satisfying \(\vert \beta \vert >\beta _{0}\) and for some Î³ satisfying
system (4), and consequently (3), is chaotic in the sense of both Devaney and LiYorke.
Proof
Lemma 1 will be used to prove this theorem. Therefore, we only need to show that the map F of system (4) satisfies all the assumptions in Lemma 1.
It is clear that \(O:=(0,\ldots,0)^{T}\in{\mathbf{R}}^{k+1}\) is always a fixed point of system (4), and other fixed points \(P:=(x_{0},\ldots,x_{0})^{T}\in{\mathbf{R}}^{k+1}\) satisfy
For simplicity, we will only prove that the fixed point O may be a regular and nondegenerate snapback repeller of the map F when parameters satisfy the conditions in Theorem 1.
For simplifying the proof and convenience, Î³ is taken as an integer and satisfies condition (5) throughout the proof.
Firstly, it is to show that O is an expanding fixed point of F in \({\mathbf{R}}^{k+1}\) under condition (5). It is obvious that F is continuously differentiable in \({\mathbf{R}}^{k+1}\), and its Jacobian matrix at O is
The characteristic equation of \(\operatorname {DF}(O)\) is
from which we obtain the result that all the eigenvalues of \(\operatorname {DF}(O)\) have absolute values larger than 1 under condition (5). If it is not true, then there will exist at least an eigenvalue \(\lambda_{0}\) of \(\operatorname {DF}(O)\) satisfies \(\vert \lambda_{0}\vert \leq1\). So, we can obtain the following contradiction:
Therefore, we find that O is an expanding fixed point of F from the first condition of Lemma 1, that is,
where \(r>0\) is a constant, \(\Vert \cdot \Vert ^{*}\) is some norm in \({\mathbf{R}}^{k+1}\), and \(\mu >1\) is an expanding coefficient of F in \(\bar{B}_{r}(O)\).
Secondly, one is to prove that O is a snapback repeller of the map F. Let \(W\subset\bar{B}_{r}(O)\) be an arbitrary neighborhood of O in \({\mathbf{R}}^{k+1}\). Then we can obtain a small interval \(U\subset{\mathbf{R}}\) containing 0 such that \(\underbrace{U\times U\times\cdots\times U}_{k+1}\subset W\). Now, one is to show that there exists a point \(O_{0}\in W\) such that \(O_{0}\neq O\) and
When \(k=1\), we can achieve a positive constant \(\beta _{1}\) such that for arbitrary \(\vert \beta \vert >\beta _{1}\), there exist two points \(x_{1},x_{2}\in U\) satisfying
Let \(O_{0}=(x_{1},x_{2})^{T}\in{\mathbf{R}}^{2}\), it follows that \(O_{0}\in U\times U\subset W\) with \(O_{0}\neq O\) for arbitrary \(\vert \beta \vert >\beta _{1}\). From (6), we obtain the result that \(F(O_{0})=(x_{2},\pi)^{T}\), \(F^{2}(O_{0})=(\pi,0)^{T}\), \(F^{3}(O_{0})=O\).
When \(k>1\), we can also achieve a positive constant \(\beta _{2}\) such that for arbitrary \(\vert \beta \vert >\beta _{2}\), there exist two points \(x_{1},x_{2}\in U\) satisfying
Let \(O_{0}=(x_{1},x_{2},0,\ldots,0)^{T}\in{\mathbf{R}}^{k+1}\), it also follows that \(O_{0}\in\underbrace{U\times U\times\cdots\times U}_{k+1}\subset W\) with \(O_{0}\neq O\) for arbitrary \(\vert \beta \vert >\beta _{2}\). From (7), we also obtain the result that \(F(O_{0})=(x_{2},0,\ldots,\pi)^{T}\), \(F^{j}(O_{0})=(0,\ldots,0,\underbrace{\pi,0,\ldots,0}_{j})^{T}\) for \(2\leq j\leq k+1\), and \(F^{k+2}(O_{0})=O\).
Set \(\beta _{0}:=\max\{\beta _{1},\beta _{2}\}\). From the above discussion, it follows that for arbitrary Î² satisfying \(\vert \beta \vert >\beta _{0}\), there exists a point \(O_{0}\in W\) satisfying \(O_{0}\neq O\) and \(F^{k+2}{(O_{0})}=O\). Therefore, O is a snapback repeller of F for arbitrary Î² satisfying \(\vert \beta \vert >\beta _{0}\).
Thirdly, one is to prove that for arbitrary \(\vert \beta \vert >\beta _{0}\), the following holds:
where \(O_{j}:=F(O_{j1})\) for \(1\leq j\leq k+1\). The existence of the Jacobian matrices of F at \(O_{j}\) (\(0\leq j\leq k+1\)) is because F is continuously differentiable in \({\mathbf{R}}^{k+1}\).
It is easy to conclude that for arbitrary \(u=(u_{1},\ldots,u_{k+1})^{T} \in{\mathbf{R}}^{k+1}\), the following holds:
When \(k=1\), it follows that \(O_{0}=(x_{1},x_{2})^{T}\), \(O_{1}=(x_{2},\pi)^{T}\), \(O_{2}=(\pi,0)^{T}\in{\mathbf{R}}^{2}\). From (6), we get \(\sin(\gamma x_{2})\neq1\) and \(\sin(x_{2}\gamma x_{1})\neq1\) for arbitrary \(\vert \beta \vert >\beta _{0}\). Together with (8), we get the following for arbitrary \(\vert \beta \vert >\beta _{0}\):
When \(k>1\), it follows that \(O_{0}=(x_{1},x_{2},0,\ldots,0)^{T}\), \(O_{1}=(x_{2},0,\ldots,0,\pi)^{T}\), and \(O_{j}=(0,\ldots,0,\underbrace{\pi,0,\ldots,0}_{j})^{T}\in {\mathbf{R}}^{k+1}\) for \(2\leq j\leq k+1\). Similarly, it follows from (7) that \(\sin(\gamma x_{1})\neq1\) and \(\sin(\gamma x_{2})\neq1\) for arbitrary \(\vert \beta \vert >\beta _{0}\). Consequently, the following hold for arbitrary \(\vert \beta \vert >\beta _{0}\):
In summary, the map F satisfies all the assumptions in Lemma 1. Consequently, system (4), i.e., (3), is chaotic in the sense of both Devaney and LiYorke. This completes the proof.â€ƒâ–¡
Remark 5
For simplifying the proof of Theorem 1, the parameter Î³ is taken as an integer. It should be pointed out that Î³ may be taken as other values such that system (4) is chaotic. In addition, it follows from the above proof that there exists a constant \(\beta _{0}>0\) such that for arbitrary \(\vert \beta \vert >\beta _{0}\), system (4) is chaotic in the sense of both Devaney and LiYorke. However, there are few methods to determine the concrete expanding area of a fixed point in the literature. So it is not easy to get the particular value \(\beta _{0}\). In practical problems, we can take the parameter \(\vert \beta \vert \) large enough such that (6) or (7) in the proof of Theorem 1 are satisfied.
For illustrating the theoretical result, we present two computer simulations of system (4), from which we can see that system (4), i.e., (3) indeed has complex dynamical behaviors. The parameters are taken as \(\alpha =0.1\), \(\beta =200\), \(\gamma =6\), \(k=1,2\). From the proof of Theorem 1, we see that O is an expanding fixed point of the map F for \(\vert \gamma \vert =6>[1+\vert \alpha +\beta \vert ]/\vert \beta \vert =1.0055\). It is also easy to obtain the result that there exist two pairs of points \(x_{1}\approx0.1388\), \(x_{2}\approx0.2618\) satisfying (6) when \(k=1\), and \(x_{1}\approx0.0026\), \(x_{2}\approx0.2618\) satisfying (7) when \(k>1\). Therefore, O is a regular and nondegenerate snapback repeller of the map F. Two simulation results are given in Figures 1 and 2 for \(k=1,2\), which exhibit complex dynamical behaviors of the system.
4 Conclusion
In this paper, we rigorously show the existence of chaos in a simple delay difference equation, which illustrates that the discrete analog of system (1) indeed has very complicated dynamical behaviors. By using the snapback repeller theory, we prove that the system is chaotic in the sense of both Devaney and LiYorke when the parameters of this system satisfy some mild conditions. Numerical simulations confirm the theoretical analysis. However, the map f of system (1) is taken as a special function. Therefore, it is very interesting to study the chaotic behavior of system (1) or its discrete analog for a more general form of f, which will be our further research.
References
UÃ§ar, A: A prototype model for chaos studies. Int. J. Eng. Sci. 40, 251258 (2002)
Gopalsamy, K, Leung, IKC: Convergence under dynamical thresholds with delays. IEEE Trans. Neural Netw. 8, 341348 (1997)
Liao, XF, Wong, KW, Leung, CS, Wu, ZF: Hopf bifurcation and chaos in a single delayed neuron equation with nonmonotonic activation function. Chaos Solitons Fractals 12, 15351547 (2001)
Zhou, SB, Liao, XF, Yu, JB: Chaotic behavior in a simplest neuron model with discrete time delay. J. Electron. Inf. Technol. 24, 13411345 (2002)
Zhou, SB, Li, H, Wu, ZF: Stability and chaos of a neural network with uncertain time delays. Lect. Notes Comput. Sci. 3496, 340345 (2005)
Hickas, JR: A Contribution to the Theory of Trade Cycle. Clarendon Press, Oxford (1965)
Blatt, JM: Dynamic Economic Systems: A PostKeynesian Approach. M. E. Sharpe, New York (1983)
Sedaghat, H: A class of nonlinear second order difference equations from macroeconomics. Nonlinear Anal. 29, 593603 (1997)
Dai, BX, Zhang, N: Stability and global attractivity for a class of nonlinear delay difference equations. Discrete Dyn. Nat. Soc. 2005, 227234 (2005)
Li, SP, Zhang, WN: Bifurcations in a secondorder difference equation from macroeconomics. J. Differ. Equ. Appl. 14, 91104 (2008)
ElMorshedy, HA: On the global attractivity and oscillations in a class of secondorder difference equations from macroeconomics. J. Differ. Equ. Appl. 17, 16431650 (2011)
Sprott, JC: A simple chaotic delay differential equation. Phys. Lett. A 366, 397402 (2007)
Zhou, ZL: Symbolic Dynamics. Shanghai Scientific and Technological Education Publishing House, Shanghai (1997)
Li, TY, Yorke, JA: Period three implies chaos. Am. Math. Mon. 82, 985992 (1975)
Devaney, RL: An Introduction to Chaotic Dynamical Systems. AddisonWesley, New York (1987)
Banks, J, Brooks, J, Cairns, G, Davis, G, Stacey, P: On Devaneyâ€™s definition of chaos. Am. Math. Mon. 99, 332334 (1992)
Huang, W, Ye, XD: Devaneyâ€™s chaos or 2scattering implies LiYorkeâ€™s chaos. Topol. Appl. 117, 259272 (2002)
Shi, YM, Chen, GR: Chaos of discrete dynamical systems in complete metric spaces. Chaos Solitons Fractals 22, 555571 (2004)
Marotto, FR: Snapback repellers imply chaos in \(R^{n}\). J. Math. Anal. Appl. 63, 199223 (1978)
Shi, YM, Chen, GR: Discrete chaos in Banach spaces. Sci. China Ser. A 34, 595609 (2004). English version: 48, 222238 (2005)
Shi, YM, Yu, P, Chen, GR: Chaotification of dynamical systems in Banach spaces. Int. J. Bifurc. Chaos 16, 26152636 (2006)
Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant 11101246) and the Postdoctoral Science Foundation of China (Grant 2014M561908).
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Li, Z., Zhu, X. Existence of chaos for a simple delay difference equation. Adv Differ Equ 2015, 39 (2015). https://doi.org/10.1186/s1366201503741
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DOI: https://doi.org/10.1186/s1366201503741