R E S E A R C H
Open Access
Distributions of zeros of solutions to first
order delay dynamic equations
D O’Regan
1, SH Saker
2, AM Elshenhab
2and RP Agarwal
3**Correspondence: [email protected]
3Department of Mathematics, Texas A&M University, Kingsvilie, TX 78363, USA
Full list of author information is available at the end of the article
Abstract
This paper is concerned with the distributions of zeros of solutions to first order delay dynamic equations on time scales. The results are obtained using iterative sequences.
MSC: 26A15; 26D10; 26D15; 39A13; 34A40; 34N05
Keywords: distribution of zeros; delay equations; time scales
1 Introduction
The oscillation and distributions of zeros of solutions of first order delay differential and difference equations are studied widely in the literature; see [–] and the references therein. However, there are only a few papers considering the distribution of zeros of so-lutions of first order delay and advanced dynamic equations on time scales (see [, ]). In [], Zhou considered the first order delay differential equation
x(t) +p(t)x(t–τ) = , fort∈[t,∞), (.)
where
t t–τ
p(s)ds≥ρ>
e, and ρ< , (.)
and established lower and upper bounds for the quotientx(t–τ)/x(t). In particular the author proved thatx(t–τ)/x(t)≥fn(ρ) andx(t–τ)/x(t) <gm(ρ), where the sequences
fn(ρ) andgn(ρ) are defined by
⎧ ⎨ ⎩
f(ρ) =eρ, fn+(ρ) =eρfn(ρ), n= , , . . . ,
g(ρ) =(–ρρ), gm+(ρ) =(–
ρ)gm(ρ)
gm(ρ)ρ+, m= , , . . . ,
and using these sequences the author studied the distribution of zeros of solutions of (.). In [], Zhang and Zhou considered the first order delay differential equation
x(t) +p(t)xτ(t)= , fort∈[t,∞), (.)
and studied the distribution of zeros of solutions using the two sequencesfn(ρ) andgm(ρ)
where ⎧ ⎨ ⎩
f(ρ) = , fn+(ρ) =eρfn(ρ), n= , , , . . . ,
g(ρ) =(–ρρ), gm+(ρ) =(–ρ)g
m(ρ)
gm(ρ)ρ+, m= , , . . . , and
t
τ(t)
p(s)ds≥ρ> , and <ρ< . (.)
Zhang and Lian in [] initiated the study of the distribution of zeros of dynamic equations on time scales and in particular, they considered the first order delay dynamic equation
x(t) +p(t)xτ(t)= , fort∈[t,∞)T, (.)
on a time scaleT, wherep∈Crd(T,R+) is a non-negative rd-continuous function,τ ∈
Crd(T,T) is strictly increasing,τ(t) <tfort∈Tandlimt→∞τ(t) =∞. In [] the authors
established lower and the upper bounds for the quotientx(τ(t))/x(t) using the sequences
fnandgmwhere
f(ρ) = , fn(ρ) =e(–ρ)fn–(ρ), n= , , . . . , (.)
and ⎧ ⎪ ⎨ ⎪ ⎩
g(ρ) =(–ρ)–ρM(–ρ), gm(ρ) =(–ρ)–M(–ρρ)+
gm–(ρ)
, m= , , . . . , (.)
and whereM< ( –ρ)/ and ≤ρ< satisfies the condition
sup λ∈E
λexp
t
τ(t)
ζμ(s)
–λp(s)s
≤ρ,
whereE={λ:λ> , –λp(t)μ(t) > };ζμ(s)andμ(s) will be defined later.
Motivated by these papers, we study the distribution of zeros of oscillatory solutions of the delay dynamic equation (.) on a time scaleTby considering new sequencesfnandgm.
In the next section, we present some basic ideas on time scales. In Section , we establish lower and upper bounds forx(τ(t))/x(t) and in Section , we study the distribution of zeros of solutions of (.).
2 Some preliminaries and lemmas
In this section, we present some preliminaries; see [, ]. A time scaleTis an arbitrary nonempty closed subset of the real numbersR. The forward and backward jump operators are defined by
withinf∅=supTandsup∅=infT. The graininess functionμon a time scaleTis defined byμ(t) :=σ(t) –t. For a functionf :T→Rthe (delta) derivative is defined by
f(t) =f(σ(t)) –f(t)
σ(t) –t ,
iff is continuous attandtis right-scattered. Iftis not right-scattered then the derivative is defined by
f(t) =lim
s→t
f(t) –f(s)
t–s ,
provided this limit exists. A functionf is said to be-differentiable if its-derivative exists. A useful formula isfσ=f(σ(t)) =f(t) +μ(t)f(t). We will make use of the following
product and quotient rules for the derivative of the productfgand the quotientf/g(where
ggσ= , and heregσ=g◦σ) of two-differentiable functionsf andg:
(fg)=fg+fσg=fg+fgσ,
f g
=f
g–fg ggσ .
Letf :R→Rbe continuously differentiable and supposeg:T→Ris delta differentiable. Thenf ◦g:T→Ris delta differentiable and the chain rule,
(f ◦g)(t) =
fg(t) +hμ(t)g(t)dh
g(t), (.)
holds. A special case of (.) is
xλ(t)=λ
hxσ + ( –h)xλ–x(t)dh.
Fors,t∈T, a functionF:T→Ris called an antiderivative off :T→RprovidedF= f(t) holds for allt∈T. In this case we define the integral off bystf(τ)τ=F(t) –F(s). Fora,b∈T, and a-differentiable functionf, the Cauchy integral off is defined by
b a f
(τ)τ=f(b) –f(a). The integration by parts formula reads
b a
f(t)g(t)t=f(t)g(t)ba– b
a
f(t)gσ(t)t,
and infinite integrals are defined as
∞
a
f(t)t= lim
b→∞
b a
f(t)t.
A functionp:T→Ris called regressive if +μ(t)p(t)= fort∈T. A functionp:T→Ris called positively regressive (we writep∈R+) if it is rd-continuous function and satisfies +
μ(t)p(t) > for allt∈T. Hilger in [] showed that forp(t) rd-continuous and regressive, the solution of the initial value problem
is given by the generalized exponential functionep(t,t), which is defined by
ep(t,t) =exp
t t
ζμ(s)
p(s)s
,
wheret,t∈T, and the cylinder transformationζh(z) is defined by
ζh(z) =
⎧ ⎨ ⎩
log(+hz)
h , ifh= ,
z, ifh= ,
wherez∈Randh∈R+.
The next lemma can be found in [].
Lemma . Assume t,t∈T.
(i)For a non-negativeϕwith–ϕ∈R+,we have the following inequality:
– t
t
ϕ(s)s≤e–ϕ(t,t)≤exp – t
t ϕ(s)s
. (.)
(ii)Ifϕis rd-continuous and non-negative,then
+ t
t
ϕ(s)s≤eϕ(t,t)≤exp
t t
ϕ(s)s
. (.)
Lemma . Assume thatTis a time scale with t∈T.If f(t) > on[t,∞)T,then
lnf(t)≤f
(t)
f(t) , for t∈[t,∞)T.
Proof Fixt. We consider two cases: (i)f(t)≤ and (ii)f(t)≥.
In the first case, we see that
hμ(t)f(t) +f(t)≤f(t).
Now recallf(σ(t)) =f(t) +μ(t)f(t) sohμ(t)f(t) +f(t) =hf(σ(t)) + ( –h)f(t) > and as
a result
hμ(t)f(t) +f(t)≥
f(t).
Apply the chain rule (.), and we get (notef(t)≤)
lnf(t)=
hμ(t)f(t) +f(t)dh
f(t)≤f (t) f(t) .
In the second case, we see that
Applying the chain rule (.), we get
lnf(t)=
hμ(t)f(t) +f(t)dh
f(t)≤f
(t) f(t) .
Thus, we deduce in both cases that
lnf(t)≤f
(t) f(t) .
The proof is complete.
Lemma . Assume that Tis a time scale with t∈T.If f(t) > and f(t)≥for t∈ [t,∞)T,then forα>
e–αf(t)≥–αe–αf(t)f(t).
Proof Sincef(t) > andf(t)≥ fort∈[t
,∞)T, we have forh∈(, )
f(t)≤hμ(t)f(t) +f(t). (.)
Applying the chain rule (.) and using (.), we see that
e–αf(t)= –α
e–α(f(t)+hμ(t)f(t))dh
f(t)≥–αe–αf(t)f(t).
The proof is complete.
3 Lower and upper bounds forx(
τ
(t))/x(t)In this section, we establish lower and upper bounds forx(τ(t))/x(t) wherex(t) is a solution of equation (.). We use the notationτ(t) =tand inductively define the iterates ofτ–i(t) by
τ–i(t) =τ–◦τ–(i–)(t), fori= , , . . . ,
whereτ–(t) is the inverse function ofτ(t). From the definition it is clear that
τ(t) <t<τ–(t) <· · ·<τ–(n–)(t) <τ–n(t) <· · ·.
To find the lower bound forx(τ(t))/x(t) we define for <ρ< a sequencefn(ρ) by
⎧ ⎨ ⎩
f(ρ) = , f(ρ) = /ρ,
fn+(ρ) =f fn(ρ)
n(ρ)+–e(–ρ)fn(ρ), n= , , , , . . . .
(.)
We note some properties offn(ρ) for the reader’s interest (see [] or use an elementary
argument using x
so there exists a functionf(ρ) such
lim
n→∞fn(ρ) =f(ρ), ≤f(ρ)≤e,
wheref(ρ) satisfies
f(ρ) =e(–ρ)f(ρ). (.)
If ( –ρ) > /e, then eitherfn(ρ) is nondecreasing andlimn→∞fn(ρ) = +∞orfn(ρ) is
nega-tive orfn(ρ) is∞after a finite numbers of terms.
Theorem . Assume thatTis a time scale and t, t,t∈T, t≥t,t≥τ–(t),x(t)
is a solution of(.)on[t,∞)T,x(t)is positive on[t,t]Tand there existsρ∈(, )with
∞>fn(ρ) > for n∈ {, , . . .}and
sup λ∈E
λexp
t
τ(t)
ζμ(s)
–λp(s)s
≤ρ for t∈τ–(t),t
T; (.)
here E={λ:λ> , –λp(t)μ(t) > for t∈[τ–(t
),t]T}.Then for n≥whenτ–(+n)(t)≤
twe have
x(τ(t))
x(t) ≥fn(ρ), for t∈
τ–(+n)(t),t
T,
where fn(ρ)is defined in(.).
Proof From (.), we see that
x(t) = –p(t)xτ(t)≤, fort∈τ–(t),t
T, (.)
so sincex(t) is nonincreasing on [τ–(t
),t]Twe have
x(τ(t))
x(t) ≥, fort∈
τ–(t),t
T. (.)
Note (.) and the fact thatxis positive on [t,t]T, so fort∈[τ–(t),t]Twe have (note
x(σ(t)) > sinceσ(t)≥t≥τ–(t ) >t)
= –μ(t)x(t) +p(t)xτ(t)
=x(t) –xσ(t)–μ(t)p(t)xτ(t)
<x(t) –μ(t)p(t)x(t)
= –μ(t)p(t)x(t).
Hence –μ(t)p(t) > fort∈[τ–(t),t]Tso –p∈R+on the interval [τ–(t),t]T. Using Lemma . (with the time scale [τ–(t
τ(t)∈[τ–(t
=x(t) +xτ(t)
The proof is complete.
thusgk(ρ) >(–ρ)–ρM(–ρ)wherek= , , . . . . Then there exists a functiong(ρ) with
lim
m→∞gm(ρ) =g(ρ) =
ρ–(M– ) – (M– )ρ–ρ.
for < –ρ≤/e(note (M– ) – (M– )ρ–ρ> if < –ρ≤/e).
Theorem . Assume thatTis a time scale and t,t∈T,t≥t,x(t)is a solution of(.)
on[t,∞)T,there exists a positive integer N≥such that x(t)is positive on[t,τ–N(t)]T
and there existsρ∈(, )with gm(ρ) > for m∈ {, , . . . ,N– }and
sup λ∈E
λexp
t
τ(t)
ζμ(s)
–λp(s)s
≤ρ for t∈τ–(t),τ–N(t)
T, (.)
where E={λ:λ> , –λp(t)μ(t) > for t∈[τ–(t
),τ–N(t)]T}and
M= sup
s∈[τ–(t
),τ–N(t)]T
p(s)μ(s) < –ρ .
Then for m∈ {, . . . ,N– }we have
x(τ(t))
x(t) <gm(ρ), for t∈
τ–(t),τ–(N–m)(t)
T,
where gm(ρ)is defined in(.).
Proof From (.), we see that
x(t)≤, fort∈τ–(t),τ–N(t)
T, (.)
and as in Theorem . notice –μ(t)p(t) > fort∈[τ–(t),τ–N(t)]Tso –p∈R+on the
interval [τ–(t
),τ–N(t)]T. From Lemma . (with the time scale [τ–(t),τ–N(t)]T) and
(.), we have fort∈[τ–(t
),τ–(N–)(t)]T(noteτ–(t)≤τ–N(t)) t
τ(t)
p(s)s≥ –ρ and
τ–(t)
t
p(s)s≥ –ρ. (.)
Lett∈[τ–(t
),τ–(N–)(t)]Tand consider G(r) :=
r t
p(s)s– +ρ, forr∈t,τ–(t)T.
NoteG: [t,τ–(t)]→Ris nondecreasing,G(t) = – +ρ< , and
Gτ–(t)= τ–(t)
t
p(s)s– +ρ≥ –ρ– +ρ= .
IfG(τ–(t)) = , then
τ–(t)
t
whereas ifG(τ–(t)) > thenG(t) < <G(τ–(t)).
and this together withxbeing nonincreasing on [τ–(t
Repeating the above procedure, we obtain fort∈[τ–(t
),τ–(N–m)(t)]T x(τ(t))
x(t) <
(ρ–g m–(ρ))
( –ρ)– M( –ρ):=gm(ρ).
The proof is complete.
4 Distributions of zeros of solutions
In this section, we study the distribution of zeros of solutions of (.) using the lower and upper bounds forx(τ(t))/x(t) in Section .
Theorem . Assume thatTis a time scale and t,t∈T,t≥t,x(t)is a solution of(.)
on[t,∞)T,and there existρ∈(, )and n,m∈ {, , . . .}with fn(ρ)≥gm(ρ),and with
N= + min
n≥,m≥
n+m:fn(ρ)≥gm(ρ)
= +n+m
assume∞>fk(ρ) > ,gk(ρ) > for n∈ {, , . . . ,N– }and
sup λ∈E
λexp
t
τ(t)
ζμ(s)
–λp(s)s
≤ρ for t∈τ–(t),τ–N(t)
T,
where E={λ:λ> , –λp(t)μ(t) > for t∈[τ–(t
),τ–N(t)]T}and
M= sup
s∈[τ–(t),τ–N(t)]T
p(s)μ(s) < –ρ .
Then every solution of(.)cannot be totally positive or totally negative on[t,τ–N(t)]T. Proof Note
fn(ρ)≥gm(ρ). (.)
Without loss of generality assumexis positive on [t,τ–N(t)]T. From Theorem . we
have
x(τ(t))
x(t) ≥fn(ρ), fort∈
τ–(+n)(t),τ–N(t)
T
and from Theorem . we have (notem=N– ( +n)≤N– )
x(τ(t))
x(t) <gm(ρ), fort∈
τ–(t),τ–(N–m
)
(t)
T.
Note sinceN= +n+mwe have (taket=τ–(N–m)
(t))
fn(ρ)≤x(
τ–(+n)(t ))
x(τ–(+n)
(t))
<gm(ρ),
Theorem . Assume thatTis a time scale and t,t∈T,t≥t,x(t)is a solution of(.)
on[t,∞)T,and there existρ∈(, )and a positive integer N≥and m∈ {, , . . . ,N– }
with
tm τ(tm)
p(s)s> –
gm(ρ)
where tm=τ
–(N–m)(t
),
and with
m= min
m∈{,...,N–} m: tm
τ(tm)
p(s)s> –
gm(ρ)
where tm=τ–(N–m)(t)
assume∞>fk(ρ) > ,gk(ρ) > for n∈ {, , . . . ,N– }and
sup λ∈E
λexp
t
τ(t)
ζμ(s)
–λp(s)s
≤ρ for t∈τ–(t),τ–N(t)
T,
where E={λ:λ> , –λp(t)μ(t) > for t∈[τ–(t),τ–N(t)]T}and
M= sup
s∈[τ–(t
),τ–N(t)]T
p(s)μ(s) < –ρ .
Then every solution of(.)cannot be totally positive or totally negative on[t,τ–N(t)]T.
Proof Note
tm
τ(tm)
p(s)s> –
gm(ρ) wheretm
=τ–(N–m )
(t). (.)
Without loss of generality assumexis positive on [t,τ–N(t)]T. From Theorem ., we
have
x(τ(t))
x(t) <gm(ρ), fort∈
τ–(t),τ–(N–m
)
(t)
T,
so in particular
x(τ(tm)) x(tm) <gm
(ρ). (.)
Integrating (.) fromτ(tm) totm, we obtain
xτ(tm)–x(tm) =
tm
τ(tm)
p(s)xτ(s)s≥xτ(tm)
tm
τ(tm)
p(s)s,
and this together with (.) gives
tm τ(tm)
p(s)s≤ – x(tm)
x(τ(tm))≤ –
gm(ρ),
Theorem . Assume thatTis a time scale and t,t∈T,t≥t,x(t)is a solution of(.)
and from Theorem ., we have
From (.) andfn∗(ρ) >fn∗–(ρ) we have
Remark . WhenT=Requation (.) is the delay differential equation
x(t) +p(t)xτ(t)= , t∈R.
Theorem . and Theorem . are related to the results in [], Lemma . and Lemma ., and Theorem . is motivated from results in [], Theorem .
Acknowledgements
The authors are grateful to the anonymous referees and the editor for their careful reading, valuable comments and correcting some errors, which have greatly improved the quality of the paper.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
The authors have contributed equally to this manuscript. They read and approved the final manuscript.
Author details
1School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland.2Department of Mathematics, Faculty of Science, Mansoura University, Mansoura, Egypt. 3Department of Mathematics, Texas A&M University, Kingsvilie, TX 78363, USA.
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Received: 26 April 2017 Accepted: 29 June 2017 References
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