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\AtBeginDocument{{\noindent\small Sixth Mississippi State
Conference on Differential Equations and Computational
Simulations, {\em Electronic Journal of Differential Equations},
Conference 15 (2007),  pp. 229--238.\newline ISSN: 1072-6691. URL:
http://ejde.mathMississippi State University\.txstate.edu or
http://ejde.math.unt.edu
\newline ftp ejde.math.txstate.edu  (login: ftp)}
\thanks{\copyright 2007 Texas State University - San Marcos.}
\vspace{9mm}}

\begin{document} \setcounter{page}{229}
\title[\hfilneg EJDE-2006/Conf/15\hfil Global attractivity]
{Global attractivity in a nonlinear difference equation}

\author[C. Qian, Y. Sun\hfil EJDE/Conf/15 \hfilneg]
{Chuanxi Qian, Yijun Sun}  % in alphabetical order

\address{Chuanxi Qian \newline
 Department of Mathematics and Statistics\\
 Mississippi State University\\
 Mississippi State, MS 39762, USA}
\email{qian@math.msstate.edu}

\address{Yijun Sun \newline
 Department of Mathematics and Statistics\\
 Mississippi State University\\
 Mississippi State, MS 39762, USA}
\email{ys101@msstate.edu}

\thanks{Published February 28, 2007.}
\subjclass[2000]{39A10} 
\keywords{Nonlinear difference equation; global attractor; 
\hfill\break\indent unimodal function; positive equilibrium}

\begin{abstract}
 In this paper, we study the asymptotic behavior of positive
 solutions of the nonlinear difference equation
 $$
 x_{n+1}=x_n f(x_{n-k}),
 $$
 where $f:[0,\infty)\to(0, \infty)$  is a unimodal
 function, and $k$ is a nonnegative integer. Sufficient
 conditions for the positive equilibrium to be a global attractor
 of all positive solutions are established. Our results can be
 applied to to some difference equations derived from mathematical
 biology.
\end{abstract}

\maketitle \numberwithin{equation}{section}
\newtheorem{theorem}{Theorem}[section]
\newtheorem{lemma}[theorem]{Lemma}
\newtheorem{corollary}[theorem]{Corollary}
\newtheorem{example}[theorem]{Example}

\section{Introduction}

Our aim in this paper is to study the global attractivity of the
 difference equation
\begin{equation}
 x_{n+1}=x_nf(x_{n-k}), \quad   n=0,1,\dots \label{e1.1}
\end{equation}
 where $ k\in \{0,1,2,\dots\}$, and
$ f:[0,\infty)\to (0,\infty) $ is a unimodal function;
 i.e, $f$ is first increasing,
and then decreasing. Global attractivity of \eqref{e1.1} under
different assumptions on $f$ has been studied by several authors,
see, for example, Kocic and Ladas \cite{k1}, Qian \cite{q1} and
Graef and Qian \cite{g2}.
 However, few results can be found under the
assumption that $f$ is a unimodal function. Besides its theoretic
interest, our motivation to study \eqref{e1.1} comes from the
following observation. Consider the delay logistic equation
\begin{equation}
x'(t)=x(t)[a+bx(t-\tau)-cx^2(t-\tau)], \quad  t\geq 0,
\label{e1.2}
\end{equation}
where
\begin{equation}
a,c,\tau\in(0,\infty) \quad \mbox{and}\quad
b\in(-\infty,\infty).\label{e1.3}
\end{equation}
This equation is a model of single species with a quadratic
per-capita growth rate (see \cite{g1} for details). One may see
\cite{h1} and \cite{l1} also for some extensions of \eqref{e1.2}.
The following difference equation with piecewise constant
arguments
\begin{equation}
x'(t)=x(t)[a+bx([t-k])-cx^2([t-k])], \quad t\geq 0, \label{e1.4}
\end{equation}
where $[\cdot]$ denotes the greatest integer function, may be
viewed as a semidiscretization of \eqref{e1.2}. By an argument
similar to that in \cite[Section 8.2]{g3}, one can see that
\eqref{e1.4} leads to the following equation
\begin{equation}
x_{n+1}=x_n e^{a+bx_{n-k}-cx_{n-k}^{2}},\quad
 n=0,1,\dots \label{e1.5}
\end{equation}
 whose oscillatory and stability properties completely
 characterize the same properties for \eqref{e1.4},
and so this leads us to study \eqref{e1.5},
 which is a special case of \eqref{e1.1}.

In the following, we only consider the positive solutions of
\eqref{e1.1}. If we let
\begin{equation}
x_{-k}, x_{-k+1}, \dots , x_0 \label{e1.6}
\end{equation}
be $k+1$ given nonnegative numbers with $x_0>0$, and $\bar{x}$ be
the unique solution of $f(x)=1$, then \eqref{e1.1} has a unique
positive solution with initial condition \eqref{e1.6}. Clearly,
$\bar{x}$ is the only positive equilibrium. In the following
section, we establish some sufficient conditions such that
$\bar{x}$ attracts all the positive solutions of \eqref{e1.1}.
Then, in Section 3, we apply our results about \eqref{e1.1} to
\eqref{e1.5} to establish some sufficient conditions for the
global attractivity of the positive equilibrium of \eqref{e1.5}.

\section{Global attractivity of \eqref{e1.1}}

Consider the difference equation
\begin{equation}
x_{n+1}=g(x_n),\quad n=1,2,\dots ,\label{e2.1}
\end{equation}
where $g\in C[R,R]$. Let $G$ be any set in $R$. We say that $V$ is
a Liapunov function for \eqref{e2.1} on $G$ if
\begin{itemize}
\item[(i)] $V$ is continuous on $G$, and \item[(ii)]
$\dot{V}(x)=V(g(x))-V(x)\leq 0 $ for all $x\in G$.
\end{itemize}

 The following lemma on the asymptotic behavior of
\eqref{e2.1} is taken from \cite{l2} and will be needed later.

\begin{lemma} \label{lem1}
Let $G$ be a bounded open positively invariant set. If
\begin{itemize} \item[(i)]  $V$ is a Liapunov function for
\eqref{e2.1} on $G$, \item[(ii)] $M\subset G$, where $M$ is the
largest invariant set of $E=\{x:\dot{V}(x)=0,  x\in \bar{G}\}$,
\item[(iii)] $V$ is constant on $M$.
\end{itemize}
Then $M$ is globally asymptotically stable relative to $G$.
\end{lemma}

The following theorem is our main result in this section.

\begin{theorem} \label{thm2.1}
Let $f:[0,\infty)\to(0,\infty)$ satisfy the following assumptions:
\begin{itemize}
\item[(i)] $f$ is a unimodal function obtaining its maximum at
$x=x^*$; \item[(ii)] $\bar{x}>x^*$ is the unique equilibrium
point; \item[(iii)] $[\ln f(x)]''\leq 0$ on $(x^*, m_0)$;
\item[(iv)] $\bar{x}f(m_0)^{k+1}\geq x^*$; \item[(v)] $f(m_0)\geq
\frac{1}{f(x^*)}$,
\end{itemize}
where $m_0=\bar{x}f(x^*)^{k+1}$. Then $\bar{x}$ is the global
attractor of all positive solutions of \eqref{e1.1}.
\end{theorem}

\begin{proof}
 First, we show that every non-oscillatory
(about $\bar{x}$) solution $\{x_n\}$ tends to $\bar{x}$. We assume
that $x_n\geq \bar{x}$ eventually. The proof for the case that
$x_n\leq \bar{x}$ eventually is similar, and so is omitted. By
\eqref{e1.1},
$$
\frac{x_{n+1}}{x_n}=f(x_{n-k}).
$$
Since for large $n$, $x_{n-k}\geq \bar{x}$, and $\bar{x}>x^*$, we
have $\frac{x_{n+1}}{x_n}\leq f(\bar{x})=1$. Hence, $\{x_n\}$ is
non-increasing and $\lim_{n\to\infty}x_n=l$ exists. Obviously,
$l=\bar{x}$.

Next, we show that every oscillatory solution tends to $\bar{x}$.
Suppose that $\{x_n\}$ is an oscillatory solution of \eqref{e1.1}.
We say that $x_s$ is a local maximum of $\{x_n\}$, if
$$
x_s\geq \bar{x},\quad   x_s\geq x_{s-1}, \quad x_s\geq x_{s+1}.
$$
Similarly, we say that $x_r$ is a local minimum of $\{x_n\}$, if
$$
x_r\leq \bar{x}, \quad x_r\leq x_{r-1}, \quad  x_r\leq x_{r+1}.
$$
By \eqref{e1.1},
$$
x_s=x_{s-1}f(x_{s-k-1})\geq x_{s-1},
$$
so we have $f(x_{s-k-1})\geq 1$, and hence $x_{s-k-1}\leq\bar{x}$.
Thus,
$$
x_s=x_{s-k-1}\prod_{i=s-k}^s
f(x_{i-k-1})\leq\bar{x}[f(x^*)]^{k+1}=m_0.
$$
So, $m_0$ is an upper bound of $\{x_n\}$.
 By a similar argument, we have
 $$
x_r\geq \bar{x}[f(m_0)]^{k+1}=m_1.
$$
 Thus, there exists some $N_0>0$, such that
 $$
m_1\leq x_n\leq m_0, \mbox{ for } n\geq N_0.
$$
 Notice that under assumption (iv), $m_1=\bar{x}f(m_0)^{k+1}\geq x^*$,
by induction, we  can prove that
$$
m_{2s+1}\leq x_n\leq m_{2s}, \quad \mbox{for } n\geq N_s
$$
 where $\{m_s\}$ is defined by
\begin{equation}
\begin{gathered}
 m_{s+1}=\bar{x}[f(m_s)]^{k+1}\\
 m_0=\bar{x}[f(x^*)]^{k+1}.
\end{gathered}\label{e2.2}
\end{equation}
To prove $x_n$ tends to $\bar{x}$, it suffices to show that $m_s$
tends to $\bar{x}$. Let $G=(0, m_0)$. Clearly, $G$ is a positively
invariant set of IVP \eqref{e2.2}. Define
$$
V(x)=\big(\ln\frac{x}{\bar{x}}\big)^2, \quad x\in G.
$$
Then
$$
\dot{V}(x) =[(k+1)\ln f(x)]^2-\big(\ln\frac{x}{\bar{x}}\big)^2.
$$
Let
$$
 g(x)= (k+1)\ln f(x).$$
 To get
$\dot{V}(x)<0$ on $G$ for $x\neq\bar{x}$, we need $
|g(x)|<|\ln\frac{x}{\bar{x}}|$, which is equivalent to
\begin{equation}
\begin{gathered}
g(x)<-\ln\frac{x}{\bar{x}}=\ln\frac{\bar{x}}{x} \quad \mbox{for } x< \bar{x};\\
 g(x)>-\ln\frac{x}{\bar{x}}=\ln\frac{\bar{x}}{x}\quad \mbox{for } x> \bar{x}.
\end{gathered}\label{e2.3}
\end{equation}
 Let $h(x)=\ln\frac{\bar{x}}{x}$.
 Observe that
\begin{equation}
g'(x)=\frac{(k+1)f'(x)}{f(x)}<0, \quad g''(x)=(k+1)(\ln
f(x))''\leq 0 \quad \mbox{on }
 (x^*, m_0); \label{e2.4}
\end{equation}
and
\begin{equation}
\big(h(x)\big)'=-\frac{1}{x}<0, \quad
\big(h(x)\big)''=\frac{1}{x^2}>0  \quad \mbox{for } x>0.
\label{e2.5}
\end{equation}
So, $g$ and $h$ look as in the following graph

\begin{figure}[ht]
\begin{center}
\includegraphics[width=0.7\textwidth]{fig1}
\end{center}
\caption{$g(x^*)= \max g(x),\  \ g(\bar{x})=h(\bar{x})$, by the
concavity of $f$ and $g$, $ h(x)>g(x) \  \ \mbox{for } x<\bar{x},\
\ h(x)<g(x) \ \ \mbox{for } x>\bar{x}$}
\end{figure}


 We first show that \eqref{e2.3} holds on $(\bar{x}, m_0)$.
 Since $g(\bar{x})=\ln\frac{\bar{x}}{\bar{x}}=0$,
by the monotonicity and concavity of $g$
 and $\ln\frac{\bar{x}}{x}$, it's enough to show that
$ g(m_0)\geq \ln(\bar{x}/m_0)$; i.e,
$$
[f(m_0)]^{k+1}\geq
\frac{\bar{x}}{m_0}=\frac{\bar{x}}{\bar{x}f(x^*)^{k+1}}
=\frac{1}{f(x^*)^{k+1}}.
$$
From (v), we can see that \eqref{e2.3} holds immediately on
$(\bar{x}, m_0)$. Furthermore, we have
$g'(x)>\big(\ln\frac{\bar{x}}{x}\big)'$ at $x=\bar{x}$. So, for
$x\in(\bar{x}, x^*)$, again by \eqref{e2.4} and \eqref{e2.5}, we
know that $g(x)>\ln\frac{\bar{x}}{x}$. For $x\leq x^*$, since $f$
is increasing and $\ln\frac{\bar{x}}{x}$ is decreasing,
\eqref{e2.3} is satisfied automatically. Thus, we have
$$
\dot{V}(x)<0 \quad\mbox{for } x\in G \quad\mbox{and} \quad
x\neq\bar{x},
$$
and
$$
E=\{x: \dot{V}(x)=0,\; x\in G\}=\{\bar{x}\}.
$$
Hence, by Lemma \ref{lem1}, $\bar{x}$ is a global attractor
relative to $G$, and so every solution $\{m_s\}$ of IVP
\eqref{e2.2} tends to $\bar{x}$. Then, it follows that $\{x_n\}$
tends to $\bar{x}$. The proof of Theorem \ref{thm2.1} is complete.
\end{proof}

We can get a linearized stability result by using the following
lemma.

\begin{lemma}[\cite{l3}] \label{lem2}
  Assume that $q\in {\bf R}$ and $k\in\{0, 1, 2,\dots\}$. Then the
delay difference equation
\begin{equation}
 x_{n+1}-x_n+qx_{n-k}=0,\quad  n=0,1,\dots\label{e2.6}
\end{equation}
is asymptotically stable if and only if
\begin{equation}
0<q<2\cos\frac{k\pi}{2k+1}.\label{e2.7}
\end{equation}
\end{lemma}

\begin{corollary} \label{coro2.1}
If the assumptions of Theorem \ref{thm2.1} hold, and
\begin{equation}
-f'(\bar{x})\bar{x}<2\cos \frac{k\pi}{2k+1}, \label{e2.8}
\end{equation}
then \eqref{e1.1} is globally asymptotically stable.
\end{corollary}

\begin{proof} Let $y_n=\ln x_n$, \eqref{e1.1} becomes
\begin{equation}
y_{n+1}-y_n-\ln f(e^{y_{n-k}})=0, \quad
 n=0,1,\dots\label{e2.9}
\end{equation}
The linearized form of \eqref{e2.9} is
\begin{equation}
 y_{n+1}-y_n-f'(\bar{x})\bar{x}y_{n-k}=0, \quad
n=0,1,\dots\label{e2.10}
\end{equation}
Let $p=-f'(\bar{x})\bar{x}$. We have $p>0$ since $f'(\bar{x})<0$.
By \eqref{e2.7}, we have that \eqref{e2.10} is stable if
\eqref{e2.8} holds. Hence, \eqref{e1.1} is locally stable. Then
combining with the global attractivity from Theorem \ref{thm2.1},
we get the global stability result.
\end{proof}

 Although we can not prove it now, we believe
that if the conditions in Theorem \ref{thm2.1} hold, then
\eqref{e2.8} holds, and so the conditions in Theorem \ref{thm2.1}
imply the global stability of \eqref{e1.1}. In Section 3, we will
show that this is true for \eqref{e1.5}.

\section{Global attractivity of \eqref{e1.5}}

In this section, we apply  our results in Section 2 to establish
some sufficient conditions for the global attarctivity of
\eqref{e1.5}. Two cases of \eqref{e1.5} with $b\leq 0$ and $b>0$ are
considered. For \eqref{e1.5}, $\bar{x}=\frac{b+\sqrt{b^2+4ac}}{2c}$
is the only positive equilibrium.

\begin{theorem} \label{thm3.1}
Assume that $b\leq 0$, and
\begin{equation}
 (k+1)a \leq \ln\frac{b+\sqrt{b^2+8ac}}{b+\sqrt{b^2+4ac}}.\label{e3.1}
\end{equation}
Then $\bar{x}$ is a global attractor of all positive solutions of
\eqref{e1.5}.
\end{theorem}

\begin{proof}
To apply Theorem \ref{thm2.1}, we need to show that all
assumptions of Theorem \ref{thm2.1} are satisfied. Here,
$f(x)=\exp\big(a+bx-cx^2\big)$, and clearly, $f(x)$ is decreasing
on $(0, \infty)$, obtaining its maximum at $x^*=0$. Note that
\begin{equation}
m_0=\bar{x}f(0)^{k+1}=\bar{x}e^{(k+1)a},\label{e3.2}
\end{equation}
and it is easy to see that assumption (ii), (iii) and (iv) of
Theorem \ref{thm2.1} are satisfied. Now, wee only need to check
(v), which is
$$
e^{a+bm_0-cm_0^2}\geq \frac{1}{e^{a}}=e^{-a},
$$
that is,
\begin{equation}
 a+bm_0-cm_0^2\geq -a.\label{e3.3}
\end{equation}
 Let $g(x)=cx^2-bx-2a$. Then $x_1=\frac{b+\sqrt{b^2+8ac}}{2c}$ is the
only positive solution of $g(x)=0$. Since $g$ is increasing on
$(0,\infty)$, \eqref{e3.3} is equivalent to $m_0\leq x_1$, which
is \eqref{e3.1}. Thus, all assumptions of Theorem \ref{thm2.1} are
satisfied, and so $\bar{x}$ is a global attractor of \eqref{e1.5}.
\end{proof}

The following result is a consequence of the above theorem and
Corollary \ref{coro2.1}.

\begin{corollary} \label{coro3.1}
If $b\leq 0$ and \eqref{e3.1} hold, then \eqref{e1.5} is globally
asymptotically stable.
\end{corollary}

\begin{proof}
By \eqref{e2.8} in Corollary \ref{coro2.1}, we need
\begin{equation}
-f'(\bar{x})\bar{x}=\frac{\sqrt{b^2+4ac}(b+\sqrt{b^2+4ac})}{2c}
<2\cos\frac{k\pi}{2k+1}.\label{e3.4}
\end{equation}
Now, we claim that \eqref{e3.1} implies \eqref{e3.4}.
 First, we want to simplify the expression. Let $A=(k+1)a$ and
$C=c/(k+1)$. From \eqref{e3.1}, it is easy to see that $ A\leq
\ln2$, and \eqref{e3.4} can be written as
\begin{equation}
\frac{\sqrt{b^2+4AC}(b+\sqrt{b^2+4AC})}{2C}<2(k+1)\cos
\frac{k\pi}{2k+1}. \label{e3.5}
\end{equation}
Next, we let
$$
B=\frac{|b|}{\sqrt C}=-\frac{b}{\sqrt C}>0.
$$
 Then \eqref{e3.5} can be written as
$$
\frac{\sqrt{B^2+4A}(-B+\sqrt{B^2+4A})}{2}<2(k+1)\cos
\frac{k\pi}{2k+1}.
$$
After simplification, this becomes
\begin{equation}
\frac{\sqrt{B^2+4A}}{B+\sqrt{B^2+4A}}A<(k+1)\cos
\frac{k\pi}{2k+1}. \label{e3.6}
\end{equation}
 Since $A\le \ln 2$, the
left hand side of Inequality \eqref{e3.6} is less than $\ln 2$. On
the other hand, the right hand side of \eqref{e3.6} can be written
as
\[
(k+1)\sin\frac{\pi}{4(k+\frac 12)}.
\]
If we use $s=k+\frac 12$, then the right hand side of Inequality
\eqref{e3.6} is
$$
g(s)=(s+\frac 12)\sin\frac{\pi}{4s},\quad s\ge \frac 12.
$$
We claim that $g$ is a decreasing function for $s\ge \frac 12$.
Observe that
$$
g'(s)=\sin\frac{\pi}{4s}-\left(\frac{\pi}{4s}+\frac{\pi}{8s^2}\right)
\cos\frac{\pi}{4s},
$$
and notice that $\frac{\pi}{4s}\geq \sin\frac{\pi}{4s}$ for
$s\geq\frac{1}{2}$,
\begin{align*}
g''(s) &=\frac{\pi}{4s^3}\cos\frac{\pi}{4s}
-\Big(\frac{\pi^2}{16s^3}+\frac{\pi^2}{32s^4}\Big)\sin\frac{\pi}{4s}\\
&\geq\frac{\pi}{4s^3}\Big[1-\left(\frac{\pi}{4s}\right)^2\Big]
-\Big(\frac{\pi^2}{16s^3}+\frac{\pi^2}{32s^4}\Big)\frac{\pi}{4s}\\
&= \frac{\pi}{4s^3}\Big(1-\frac{\pi^2}{16s^2}-\frac{\pi^2}{16s}
-\frac{\pi^2}{32s^2}\Big)\\
&\geq \frac{\pi}{4s^3}\Big(1-\frac{\pi^2}{12}\Big)>0.
\end{align*}
So $g'$ is increasing,
$\max_{s\geq\frac12}g'(s)=\lim_{s\to\infty}g'(s)=0$, and $g$ is
decreasing for $s\geq \frac12$.  We get
$$
\min_{s\geq\frac12}g(s)=\lim_{s\to\infty}(s+\frac
12)\sin\frac{\pi}{4s} =\frac{\pi}4,
$$
which is greater than $\ln 2$. Thus \eqref{e3.6} holds, and
therefore \eqref{e3.4} holds. The proof is complete.
\end{proof}

 \begin{example} \label{exa1} \rm
 Consider the difference equation
$$
x_{n+1}=x_ne^{0.1-x_{n-1}-x_{n-1}^2}.
$$
Here $k=1$, $a=0.1$, $b=-1$, $c=1$, and
$$
(k+1)a=.2<\ln\frac{b+\sqrt{b^2+8ac}}{b+\sqrt{b^2+4ac}}\approx
0.623.
$$
 Hence, by Corollary \ref{coro3.1}, $\bar{x}$ is globally asymptotically stable.
\end{example}

\begin{theorem} \label{thm3.2}
Assume $b> 0$ and
\begin{equation}
\frac{(k+1)D}{4c}\leq \ln\frac{b+\sqrt{2D}}{b+\sqrt{D}},
\label{e3.7}
\end{equation}
where $D=b^2+4ac$. Then all positive solutions of \eqref{e1.5}
tend to $\bar{x}$.
\end{theorem}

\begin{proof}
Let $f(x)=\exp\big(a+bx-cx^2\big)$. We show that $f$ satisfies all
the conditions assumed in Theorem \ref{thm2.1}. Clearly, $f$ is
increasing on $(0, x^*)$ and decreasing on $(x^*, \infty)$, where
$x^*=\frac{b}{2c}$, and so assumption (i) is satisfied. (ii) and
(iii) are also easy to check. We see that to have
$\bar{x}f(m_0)^{k+1}\geq x^*$, we need
\begin{equation}
(a+bm_0-cm_0^2)\geq
\frac{1}{k+1}\ln\frac{b}{b+\sqrt{D}}.\label{e3.8}
\end{equation}
By a direct but tedious calculation, \eqref{e3.8} is equivalent to
\begin{equation}
\frac{(k+1)D}{4c}\leq
\ln\frac{b+\sqrt{D+\frac{4c}{k+1}\ln\frac{b+\sqrt{D}}{b}}}{b+\sqrt{D}}.
\label{e3.9}
\end{equation}
We claim that \eqref{e3.7} implies \eqref{e3.9}. To prove our
claim, it suffices to show
$$
\frac{b+\sqrt{2D}}{b+\sqrt{D}}\leq
\frac{b+\sqrt{D+\frac{4c}{k+1}\ln\frac{b+\sqrt{D}}{b}}}{b+\sqrt{D}},
$$
which is equivalent to
$$
\sqrt{2D}\leq \sqrt{D+\frac{4c}{k+1}\ln\frac{b+\sqrt{D}}{b}},
$$
that is
$$
\frac{(k+1)D}{4c}\leq \ln\frac{b+\sqrt{D}}{b}.
$$
By \eqref{e3.7}, it is sufficient to show that
\begin{equation}
\ln\frac{b+\sqrt{2D}}{b+\sqrt{D}}\leq \ln\frac{b+\sqrt{D}}{b}.
\label{e3.10}
\end{equation}
It is not difficult to see that \eqref{e3.10} is equivalent to
$$
\frac{\sqrt{2}-1}{b+\sqrt{D}}\leq \frac{1}{b},
$$
which is obviously true. Thus, (iv) is satisfied.

To check (v), we need $\exp\big(a+bm_0-cm_0^2)\geq
\exp\big(-(a+bx^*-cx^{*2})\big)$; i.e,
\begin{equation}
 a+bm_0-cm_0^2\geq -\frac{D}{4c}.\label{e3.11}
\end{equation}
Let
\begin{equation}
h(x)=a+bx-cx^2+\frac{D}{4c}.\label{e3.12}
\end{equation}
We see that the positive solution of \eqref{e3.12} is
$x_2=\frac{b+\sqrt{2D}}{2c}$. Since both $m_0$ and $x_2$ are
larger than $x^*$, and on $(x^*,\infty)$, $h$ is decreasing,
\eqref{e3.11} is equivalent to $m_0\leq x_2$, which is satisfied
by \eqref{e3.7}. Hence, it follows  by Theorem \ref{thm2.1} that
$\{x_n\}$ tends to $\bar{x}$.
\end{proof}

\begin{corollary} \label{coro3.2}
Assume that  \eqref{e3.7} holds.  Then \eqref{e1.5} is globally
asymptotically stable.
\end{corollary}

 \begin{proof} By condition \eqref{e2.8} in Corollary \ref{coro2.1}, we
 need
$$ -f'(\bar{x})\bar{x}=\frac{\sqrt{D}(b+\sqrt{D})}{2c}
 <2\cos\frac{k\pi}{2k+1},
$$
 which is equivalent to
$$
 \frac{D}{4c}<\cos\frac{k\pi}{2k+1}-\frac{b\sqrt{D}}{4c}.
$$
 Then, combining this with Theorem \ref{thm3.2}, we know that  if
\begin{equation}
\frac{D}{4c}\leq
 \min\{\frac{1}{k+1}\ln\frac{b+\sqrt{2D}}{b+\sqrt{D}},
 \cos\frac{k\pi}{2k+1}-\frac{b\sqrt{D}}{4c}\}\label{e3.13}
\end{equation}
holds, then \eqref{e1.5} is globally asymptotically stable.
 Now, we show that
\begin{equation}
\frac{1}{k+1}\ln \frac{b+\sqrt {2D}}{b+\sqrt D}\le \cos
\frac{k\pi}{2k+1}-\frac{b\sqrt D}{4c}, \label{e3.14}
\end{equation}
under the assumption \eqref{e3.7}. Observe that
$$
\frac{b\sqrt D}{4c}=\frac{b}{\sqrt D}\frac{D}{4c}\le
\frac{b}{\sqrt D}\frac{1}{k+1}\ln \frac{b+\sqrt {2D}}{b+\sqrt D}
$$
by \eqref{e3.7}. So it suffices to show that
$$
(\frac{b}{\sqrt D}+1)\frac 1{k+1}\ln \frac{b+\sqrt {2D}}{b+\sqrt
D} \le \cos \frac{k\pi}{2k+1}.
$$
After simplification, this becomes
$$
(\frac{b}{\sqrt D}+1)\ln \frac{b+\sqrt {2D}}{b+\sqrt D} \le
(k+1)\sin \frac{\pi}{4k+2} .
$$
Let $\frac b{\sqrt D}=t$ ($0<t<1$) and $s=k+\frac 12$ ($s\ge \frac
12$). It is sufficient to show that
\begin{equation}
(t+1)\ln \frac{t+\sqrt 2}{t+1}\le (s+\frac 12)\sin
\frac{\pi}{4s}.\label{e3.15}
\end{equation}
If the maximum of the function of $t$ is less than the minimum of
the function of $s$, then we are done. Let
$$
f(t)=(t+1)\ln \frac{t+\sqrt 2}{t+1}, \quad g(s)=(s+\frac 12)\sin
\frac{\pi}{4s}.
$$
We claim that $f$ is increasing on $(0,1)$. To this end, observe
that
$$
f'(t)=\ln\frac{t+\sqrt{2}}{t+1}-\frac{\sqrt{2}-1}{t+\sqrt{2}},\quad
f''(t)=\frac{2\sqrt{2}-3}{(t+\sqrt{2})^2(t+1)}<0.
$$
Since $f'$ is decreasing and $\min_{0<t<1}
f'(t)=f'(1)\approx0.0166>0$, $f$ is increasing for $0<t<1$. We
know from the proof of Corollary \ref{coro3.1} that $g$ is
decreasing on $(\frac{1}{2}, \infty)$.
 It is easy to see that
$\max_{0<t<1}f(t)=f(1)\approx0.376$ and $\min_{s\geq
\frac{1}{2}}g(s)=\lim_{s\to\infty}g(s)\approx0.786$. Thus, we have
$f(t)\leq g(s)$ always; i.e, \eqref{e3.15} holds. The proof of
Corollary \ref{coro3.2} is complete.
\end{proof}

\begin{example} \label{exa2} \rm
Consider the difference equation
$$
x_{n+1}=x_ne^{0.01+x_{n-3}-20 x_{n-3}^2}.
$$
Here $ a=.01$, $b=1$,  $c=20$ and $k=3$. So
$$
\frac{(k+1)D}{4c}\approx .09\leq
\ln\frac{b+\sqrt{2D}}{b+\sqrt{D}}\approx .825.
$$
 By Corollary \ref{coro3.2}, $\bar{x}$ is globally
 asymptotically stable.
\end{example}

\section{Remarks}
 Consider the difference equation
\begin{equation}
x_{n+1}-x_n=x_n(a+bx_{n-k}-cx_{n-k}^2), \label{e4.1}
\end{equation}
where $a, c\in(0,\infty)$, $b\in (-\infty, +\infty)$, and $k\in
\{0, 1,\dots\}$. Equation \eqref{e4.1} may be viewed as a discrete
analogue of the delay differential equation \eqref{e1.3}. The
global attractivity of the positive equilibrium when $k=0$ was
investigated by Rodrigues \cite{r1}.  Kocic and Ladas \cite{k2},
posted the following research projects: Obtain a global stability
result for the positive equilibrium $\bar{x}$ of \eqref{e4.1} when
$k\geq 1$, and obtain explicit sufficient conditions on $a, b, c$
and $k$ so that all solutions of \eqref{e4.1} with appropriate
initial condition remain positive for all $n\geq 0$. By using an
argument similar to one in this paper, we can establish a
sufficient condition for the positive equilibrium $\bar{x}$ to be
a global attractor of all positive solutions of \eqref{e4.1}. Then
together with the linearized stability result, we can obtain a
global stability result for the positive equilibrium $\bar{x}$ of
\eqref{e4.1} when $k\geq 1$. However, the problem that how to
obtain explicit sufficient condition so that all solutions remain
positive for all $n\geq 0$ remains open.

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\end{document}
